Computational studies in human African trypanosomiasis
- Authors: Muronzi, Tendai
- Date: 2023-10-13
- Subjects: African trypanosomiasis , Apolipoprotein L1 , Docking , Protein-protein interactions , Homology modeling , Tetrahydrofolate dehydrogenase , Pteridine reductase
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/431883 , vital:72812 , DOI 10.21504/10962/431885
- Description: Human African trypanosomiasis (HAT) is a neglected tropical disease (NTD) caused by two subspecies of the parasite, namely Trypanosoma brucei (Tb) gambiense (g-HAT) and rhodesiense (r-HAT). HAT is endemic in sub-Saharan countries, where the parasite transmission vectors, tsetse flies, breed. An estimated 70 million people remain at risk of contracting the disease, where the infection is classified as acute or chronic for g-HAT and r-HAT, respectively, with both forms ending in fatal meningoencephalitis when left untreated. Both g-HAT and r-HAT are responsible for widespread fatal epidemics throughout sub-Saharan African history, resulting from the complex molecular interplay between trypanosomes and humans through unique, innate immunity evasion mechanisms. Of interest, the Tbr subspecies expresses a serum resistance-associated protein (SRA), which binds to human serum lytic factor, apolipoprotein L1 (ApoL1), nullifying any trypanocidal activity. In response, ApoL1 (G1 and G2) variants found in humans of sub-Saharan African lineage have been cited for conferring resistance to the r-HAT infection in an interaction that is not fully elucidated In the event of successful infection, current HAT chemotherapeutics are plagued with complexity of administration, poor efficacy, toxicity, and potential drug resistance, highlighting a need for improved approaches. The parasite folate pathway provides a strategic target for alternative anti-trypanosomal drug development as trypanosomatids are folate auxotrophs, requiring host folate for growth and survival. Validated drug targets pteridine reductase (TbPTR1) and dihydrofolate reductase (TbDHFR) are essential for salvaging cofactors folate and folate biopterin crucial to parasite survival, making them viable targets for anti-folate investigation. The overall aims of this thesis were to a) provide insights into the molecular and dynamic basis of the SRA and ApoL1 interplay in HAT infection and b) identify safer and more efficient anti-folate anti-trypanosomal drug alternatives through in silico approaches. To achieve our first aim, in silico structure prediction was applied to generate 3D models of ApoL1 C-terminal variants G0, G1, G1G/M, G2 and G1G2, and four SRA variants retrieved from the NCBI database. The SRA and ApoL1 structures were inspected dynamically to identify the effect of the variants through molecular dynamics (MD) simulations. Dynamic residue network (DRN) analysis of MD trajectories was fundamental in identifying residues playing a vital role in the intramolecular communication of both proteins in the presence of mutations. Protein-protein docking was then applied to calculate plausible SRA-ApoL1 C-terminal wild-type complex structures to further elucidate the nature of SRA-mediated infection. Through MD simulations, twelve SRA-ApoL1 dimeric structures were narrowed down from five to two energetically sound complexes. The two feasible SRA-ApoL1 complexes (1 and 2) exhibited favourable communication observed through DRN analysis, including the retaining key communication residues identified in prior monomer DRN calculations. ApoL1 C-terminal variants were additionally incorporated into SRA-ApoL1 complexes 1 and 2 for further complex dynamics analysis This investigation into the nature of SRA-ApoL1 binding resulted in five primary outcomes: 1) highlighting the intramolecular effects ApoL1 variants have on the stability of the protein, 2) the identification of crucial SRA and ApoL1 communication residues in both monomeric or dimeric form, 3) the isolation of feasible SRA-ApoL1 complexes determined through global and local structural analyses 4) identification of residues crucial to the complex formation and maintenance of SRA-ApoL1, overlapping with those identified in (1), and 5) the minimal dissociative role of the G1 mutations in the complex, but compounding effect of the G2 deletion mutation. Computational modelling and drug repurposing were employed to achieve the thesis's second aim as they drastically cut down the costs involved in drug discovery and provide a more time-efficient screening method through numerous drug candidates. Using high throughput virtual screening, a subset of 2089 approved DrugBank compounds were screened against TbPTR1. The outputs were filtered to 24 viable compounds in 54 binding poses using binding energy and molecular interactions. Through subsequent MD simulations of 200ns, thirteen potential hit compounds were identified. The resultant hit compounds were subjected to further blind docking against TbDHFR and molecular dynamics to identify compounds with the potential for dual inhibition. The filtered subset was also tested in in vitro single concentration and dose-response bioassays to assess inhibitory properties against Trypanosoma brucei, complementing in silico findings. Post-molecular dynamics, four compounds exhibited high stabilities and molecular interactions with both TbPTR1 and TbDHFR, with two presenting favourable results in the in vitro assays. Three compounds additionally shared common structural moieties. In all, the in silico repurposing highlighted drugs characterised by favourable interactions and stabilities in TbPTR1, thus providing (1) a framework for further studies investigating anti-folate HAT compounds and (2) modulatory scaffolds based on identified moieties that can be used for the design of safe anti-folate trypanosomal drugs. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2023
- Full Text:
- Authors: Muronzi, Tendai
- Date: 2023-10-13
- Subjects: African trypanosomiasis , Apolipoprotein L1 , Docking , Protein-protein interactions , Homology modeling , Tetrahydrofolate dehydrogenase , Pteridine reductase
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/431883 , vital:72812 , DOI 10.21504/10962/431885
- Description: Human African trypanosomiasis (HAT) is a neglected tropical disease (NTD) caused by two subspecies of the parasite, namely Trypanosoma brucei (Tb) gambiense (g-HAT) and rhodesiense (r-HAT). HAT is endemic in sub-Saharan countries, where the parasite transmission vectors, tsetse flies, breed. An estimated 70 million people remain at risk of contracting the disease, where the infection is classified as acute or chronic for g-HAT and r-HAT, respectively, with both forms ending in fatal meningoencephalitis when left untreated. Both g-HAT and r-HAT are responsible for widespread fatal epidemics throughout sub-Saharan African history, resulting from the complex molecular interplay between trypanosomes and humans through unique, innate immunity evasion mechanisms. Of interest, the Tbr subspecies expresses a serum resistance-associated protein (SRA), which binds to human serum lytic factor, apolipoprotein L1 (ApoL1), nullifying any trypanocidal activity. In response, ApoL1 (G1 and G2) variants found in humans of sub-Saharan African lineage have been cited for conferring resistance to the r-HAT infection in an interaction that is not fully elucidated In the event of successful infection, current HAT chemotherapeutics are plagued with complexity of administration, poor efficacy, toxicity, and potential drug resistance, highlighting a need for improved approaches. The parasite folate pathway provides a strategic target for alternative anti-trypanosomal drug development as trypanosomatids are folate auxotrophs, requiring host folate for growth and survival. Validated drug targets pteridine reductase (TbPTR1) and dihydrofolate reductase (TbDHFR) are essential for salvaging cofactors folate and folate biopterin crucial to parasite survival, making them viable targets for anti-folate investigation. The overall aims of this thesis were to a) provide insights into the molecular and dynamic basis of the SRA and ApoL1 interplay in HAT infection and b) identify safer and more efficient anti-folate anti-trypanosomal drug alternatives through in silico approaches. To achieve our first aim, in silico structure prediction was applied to generate 3D models of ApoL1 C-terminal variants G0, G1, G1G/M, G2 and G1G2, and four SRA variants retrieved from the NCBI database. The SRA and ApoL1 structures were inspected dynamically to identify the effect of the variants through molecular dynamics (MD) simulations. Dynamic residue network (DRN) analysis of MD trajectories was fundamental in identifying residues playing a vital role in the intramolecular communication of both proteins in the presence of mutations. Protein-protein docking was then applied to calculate plausible SRA-ApoL1 C-terminal wild-type complex structures to further elucidate the nature of SRA-mediated infection. Through MD simulations, twelve SRA-ApoL1 dimeric structures were narrowed down from five to two energetically sound complexes. The two feasible SRA-ApoL1 complexes (1 and 2) exhibited favourable communication observed through DRN analysis, including the retaining key communication residues identified in prior monomer DRN calculations. ApoL1 C-terminal variants were additionally incorporated into SRA-ApoL1 complexes 1 and 2 for further complex dynamics analysis This investigation into the nature of SRA-ApoL1 binding resulted in five primary outcomes: 1) highlighting the intramolecular effects ApoL1 variants have on the stability of the protein, 2) the identification of crucial SRA and ApoL1 communication residues in both monomeric or dimeric form, 3) the isolation of feasible SRA-ApoL1 complexes determined through global and local structural analyses 4) identification of residues crucial to the complex formation and maintenance of SRA-ApoL1, overlapping with those identified in (1), and 5) the minimal dissociative role of the G1 mutations in the complex, but compounding effect of the G2 deletion mutation. Computational modelling and drug repurposing were employed to achieve the thesis's second aim as they drastically cut down the costs involved in drug discovery and provide a more time-efficient screening method through numerous drug candidates. Using high throughput virtual screening, a subset of 2089 approved DrugBank compounds were screened against TbPTR1. The outputs were filtered to 24 viable compounds in 54 binding poses using binding energy and molecular interactions. Through subsequent MD simulations of 200ns, thirteen potential hit compounds were identified. The resultant hit compounds were subjected to further blind docking against TbDHFR and molecular dynamics to identify compounds with the potential for dual inhibition. The filtered subset was also tested in in vitro single concentration and dose-response bioassays to assess inhibitory properties against Trypanosoma brucei, complementing in silico findings. Post-molecular dynamics, four compounds exhibited high stabilities and molecular interactions with both TbPTR1 and TbDHFR, with two presenting favourable results in the in vitro assays. Three compounds additionally shared common structural moieties. In all, the in silico repurposing highlighted drugs characterised by favourable interactions and stabilities in TbPTR1, thus providing (1) a framework for further studies investigating anti-folate HAT compounds and (2) modulatory scaffolds based on identified moieties that can be used for the design of safe anti-folate trypanosomal drugs. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2023
- Full Text:
Falcipain 2 and 3 as malarial drug targets: deciphering the effects of missense mutations and identification of allosteric modulators via computational approaches
- Authors: Okeke, Chiamaka Jessica
- Date: 2023-10-13
- Subjects: Antimalarials , Cysteine proteinases , Missense mutation , Allostery , Cysteine proteinase falcipain 2a , Cysteine proteinase falcipain 3
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/432170 , vital:72848 , DOI 10.21504/10962/432170
- Description: Malaria, caused by an obligate unicellular protozoan parasite of the genus Plasmodium, is a disease of global health importance that remains a major cause of morbidity and mortality in developing countries. The World Health Organization (WHO) reported nearly 247 million malaria cases in 2021, causing 619,000 deaths, the vast majority ascribed to pregnant women and young children in sub-Saharan Africa. A critical component of malaria mitigation and elimination efforts worldwide is antimalarial drugs. However, resistance to available antimalarial drugs jeopardizes the treatment, prevention, and eradication of the disease. The recent emergence and spread of resistance to artemisinin (ART), the currently recommended first-line antimalarial drug, emphasizes the need to understand the resistance mechanism and apply this knowledge in developing new drugs that are effective against malaria. An insight into ART's mechanism of action indicates that ferrous iron (Fe2+) or heme, released when hemoglobin is degraded, cleaves the endoperoxide bridge. As a result, free radicals are formed, which alkylate many intracellular targets and result in plasmodial proteopathy. Aside from the existing evidence that mutations in the Kelch 13 protein propeller domain affect ART sensitivity and clearance rate by Plasmodium falciparum (Pf) parasites, recent investigations raise the possibility that additional target loci may be involved, and these include a nonsense (S69stop) and four missense variants (K255R, N257E, T343P, and D345G) in falcipain 2 (FP-2) protein. FP-2 and falcipain 3 (FP-3) are cysteine proteases responsible for hydrolyzing hemoglobin in the host erythrocytic cycle, a key virulence factor for malaria parasite growth and metabolism. Due to the obligatory nature of the hemoglobin degradation process, both proteases have become potential antimalarial drug targets attracting attention in recent years for the development of blood-stage antimalarial drugs. The alteration of the expression profile of FP-2 and FP-3 through gene manipulation approaches (knockout) or compound inhibition assays, respectively, induced parasites with swollen food vacuoles due to the accumulation of undegraded hemoglobin. Furthermore, missense mutations in FP-2 confer parasites with decreased ART sensitivity, probably due to altered enzyme efficiency and momentary decreased hemoglobin degradation. Hence, understanding how these mutations affect FP-2 (including those implicated in ART resistance) and FP-3 is imperative to finding potentially effective inhibitors. The first aim of this thesis is to characterize the effects of missense mutations on the partial zymogen complex and the catalytic domain of FP-2 and FP-3 using a range of computational approaches and tools such as homology modeling, molecular dynamics (MD) simulations, comparative essential dynamics, dynamic residue network (DRN) analysis, weighted residue contact map analysis, amongst others. The Pf genomic resource database (PlasmoDB) identified 41 missense mutations located in the partial zymogen and catalytic domains of FP-2 and FP-3. Using structure-based tools, six putative allosteric pockets were identified in FP-2 and FP-3. The effect of mutations on the whole protein, the central core, binding pocket residues and allosteric pockets was evaluated. The accurate 3D homology models of the WT and mutants were calculated. MD simulations were performed on the various systems as a quick starting point. MD simulations have provided a cornerstone for establishing numerous computational tools for describing changes arising from mutations, ligand binding, and environmental changes such as pH and temperature. Post-MD analysis was performed in two stages viz global and local analysis. Global analysis via radius of gyration (Rg) and comparative essential dynamic analysis revealed the conformational variability associated with all mutations. In the catalytic domain of FP-2, the presence of M245I mutation triggered the formation of a cryptic pocket via an exclusive mechanism involving the fusion of pockets 2 and 6. This striking observation was also detected in the partial zymogen complex of FP-2 and induced by A159V, M245I and E249A mutations. A similar observation was uncovered in the presence of A422T mutation in the catalytic domain of FP-3. Local DRN and contact map analyses identified conserved inter-residue interaction changes on important communication networks. This study brings a novel understanding of the effects of missense mutations in FP-2 and FP-3 and provides important insight which may help discover new anti-hemoglobinase drugs. The second aim is the identification of potential allosteric ligands against the WT and mutant systems of FP-2 and FP-3 using various computational tools. Of the six potential allosteric pockets identified in FP-2 and FP-3, pocket 1 was evaluated by SiteMap as the most druggable in both proteins. This pipeline was implemented to screen pocket 1 of FP-2 and FP-3 against 2089 repositionable compounds obtained from the DrugBank database. In order to ensure selectivity and specificity to the Plasmodium protein, the human homologs (Cat K and Cat L) were screened, and compounds binding to these proteins were exempted from further analysis. Subsequently, eight compounds (DB00128, DB00312, DB00766, DB00951, DB02893, DB03754, DB13972, and DB14159) were identified as potential allosteric hits for FP-2 and five (DB00853, DB00951, DB01613, DB04173 and DB09419) for FP-3. These compounds were subjected to MD simulation and post-MD trajectory analysis to ascertain their stability in their respective protein structures. The effects of the stable compounds on the WT and mutant systems of FP-2 and FP-3 were then evaluated using DRN analysis. Attention has recently been drawn towards identifying novel allosteric compounds targeting FP-2 and FP-3; hence this study explores the potential allosteric inhibitory mechanisms in the presence and absence of mutations in FP-2 and FP-3. Overall, the results presented in this thesis provide (i) an understanding of the role mutations in the partial zymogen complex play in the activation of the active enzyme, (ii) an insight into the possible allosteric mechanisms induced by mutations on the active enzymes, and (iii) a computational pipeline for the development of novel allosteric modulators for malaria inhibition studies. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2023
- Full Text:
- Authors: Okeke, Chiamaka Jessica
- Date: 2023-10-13
- Subjects: Antimalarials , Cysteine proteinases , Missense mutation , Allostery , Cysteine proteinase falcipain 2a , Cysteine proteinase falcipain 3
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/432170 , vital:72848 , DOI 10.21504/10962/432170
- Description: Malaria, caused by an obligate unicellular protozoan parasite of the genus Plasmodium, is a disease of global health importance that remains a major cause of morbidity and mortality in developing countries. The World Health Organization (WHO) reported nearly 247 million malaria cases in 2021, causing 619,000 deaths, the vast majority ascribed to pregnant women and young children in sub-Saharan Africa. A critical component of malaria mitigation and elimination efforts worldwide is antimalarial drugs. However, resistance to available antimalarial drugs jeopardizes the treatment, prevention, and eradication of the disease. The recent emergence and spread of resistance to artemisinin (ART), the currently recommended first-line antimalarial drug, emphasizes the need to understand the resistance mechanism and apply this knowledge in developing new drugs that are effective against malaria. An insight into ART's mechanism of action indicates that ferrous iron (Fe2+) or heme, released when hemoglobin is degraded, cleaves the endoperoxide bridge. As a result, free radicals are formed, which alkylate many intracellular targets and result in plasmodial proteopathy. Aside from the existing evidence that mutations in the Kelch 13 protein propeller domain affect ART sensitivity and clearance rate by Plasmodium falciparum (Pf) parasites, recent investigations raise the possibility that additional target loci may be involved, and these include a nonsense (S69stop) and four missense variants (K255R, N257E, T343P, and D345G) in falcipain 2 (FP-2) protein. FP-2 and falcipain 3 (FP-3) are cysteine proteases responsible for hydrolyzing hemoglobin in the host erythrocytic cycle, a key virulence factor for malaria parasite growth and metabolism. Due to the obligatory nature of the hemoglobin degradation process, both proteases have become potential antimalarial drug targets attracting attention in recent years for the development of blood-stage antimalarial drugs. The alteration of the expression profile of FP-2 and FP-3 through gene manipulation approaches (knockout) or compound inhibition assays, respectively, induced parasites with swollen food vacuoles due to the accumulation of undegraded hemoglobin. Furthermore, missense mutations in FP-2 confer parasites with decreased ART sensitivity, probably due to altered enzyme efficiency and momentary decreased hemoglobin degradation. Hence, understanding how these mutations affect FP-2 (including those implicated in ART resistance) and FP-3 is imperative to finding potentially effective inhibitors. The first aim of this thesis is to characterize the effects of missense mutations on the partial zymogen complex and the catalytic domain of FP-2 and FP-3 using a range of computational approaches and tools such as homology modeling, molecular dynamics (MD) simulations, comparative essential dynamics, dynamic residue network (DRN) analysis, weighted residue contact map analysis, amongst others. The Pf genomic resource database (PlasmoDB) identified 41 missense mutations located in the partial zymogen and catalytic domains of FP-2 and FP-3. Using structure-based tools, six putative allosteric pockets were identified in FP-2 and FP-3. The effect of mutations on the whole protein, the central core, binding pocket residues and allosteric pockets was evaluated. The accurate 3D homology models of the WT and mutants were calculated. MD simulations were performed on the various systems as a quick starting point. MD simulations have provided a cornerstone for establishing numerous computational tools for describing changes arising from mutations, ligand binding, and environmental changes such as pH and temperature. Post-MD analysis was performed in two stages viz global and local analysis. Global analysis via radius of gyration (Rg) and comparative essential dynamic analysis revealed the conformational variability associated with all mutations. In the catalytic domain of FP-2, the presence of M245I mutation triggered the formation of a cryptic pocket via an exclusive mechanism involving the fusion of pockets 2 and 6. This striking observation was also detected in the partial zymogen complex of FP-2 and induced by A159V, M245I and E249A mutations. A similar observation was uncovered in the presence of A422T mutation in the catalytic domain of FP-3. Local DRN and contact map analyses identified conserved inter-residue interaction changes on important communication networks. This study brings a novel understanding of the effects of missense mutations in FP-2 and FP-3 and provides important insight which may help discover new anti-hemoglobinase drugs. The second aim is the identification of potential allosteric ligands against the WT and mutant systems of FP-2 and FP-3 using various computational tools. Of the six potential allosteric pockets identified in FP-2 and FP-3, pocket 1 was evaluated by SiteMap as the most druggable in both proteins. This pipeline was implemented to screen pocket 1 of FP-2 and FP-3 against 2089 repositionable compounds obtained from the DrugBank database. In order to ensure selectivity and specificity to the Plasmodium protein, the human homologs (Cat K and Cat L) were screened, and compounds binding to these proteins were exempted from further analysis. Subsequently, eight compounds (DB00128, DB00312, DB00766, DB00951, DB02893, DB03754, DB13972, and DB14159) were identified as potential allosteric hits for FP-2 and five (DB00853, DB00951, DB01613, DB04173 and DB09419) for FP-3. These compounds were subjected to MD simulation and post-MD trajectory analysis to ascertain their stability in their respective protein structures. The effects of the stable compounds on the WT and mutant systems of FP-2 and FP-3 were then evaluated using DRN analysis. Attention has recently been drawn towards identifying novel allosteric compounds targeting FP-2 and FP-3; hence this study explores the potential allosteric inhibitory mechanisms in the presence and absence of mutations in FP-2 and FP-3. Overall, the results presented in this thesis provide (i) an understanding of the role mutations in the partial zymogen complex play in the activation of the active enzyme, (ii) an insight into the possible allosteric mechanisms induced by mutations on the active enzymes, and (iii) a computational pipeline for the development of novel allosteric modulators for malaria inhibition studies. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2023
- Full Text:
In silico characterization of missense mutations in infectious diseases: case studies of tuberculosis and COVID-19
- Authors: Barozi, Victor
- Date: 2023-10-13
- Subjects: Microbial mutation , COVID-19 (Disease) , Drug resistance in microorganisms , Antitubercular agents , Tuberculosis , Molecular dynamics , Single nucleotide polymorphisms
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/431626 , vital:72791 , DOI 10.21504/10962/431626
- Description: One of the greatest challenges facing modern medicine and the global public health today is antimicrobial drug resistance (AMR). This “silent pandemic,” as coined by the world health organization (WHO), is steadily increasing with an estimated 4.95 million mortalities attributed to AMR in 2019, 1.27 million of which were directly linked to AMR. Some of the contributors to AMR include self-prescription, drug overuse, sub-optimal drug prescriptions by health workers, and inaccessibility to drugs, especially in remote areas, which leads to poor adherence. The situation is aggravated by the upsurge of new zoonotic infections like the coronavirus disease 2019, which present unique challenges and take the bulk of resources hence stunting the fight against AMR. Quite alarming still is our current antimicrobial arsenal, which hasn’t had any novel antimicrobial drug discovery/addition, of a new class, since the 1980s. This puts a burden on the existing broad-spectrum antimicrobial drugs which are already struggling against multi-drug resistant strains like multi-drug resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB). Besides the search for new antimicrobial agents, the other avenue for addressing AMR is studying drug resistance mechanisms, especially single nucleotide polymorphisms (SNPs), that change drug target characteristics. With the advancement of computational power and data storage resources, computational approaches can be applied in mutational studies to provide insight into the drug resistance mechanisms with an aim to inform future drug design and development. Therefore, in the first part of this thesis, we employ integrative in silico approaches, including 3D structure modeling, molecular dynamic (MD) simulations, comparative essential dynamics (ED), and protein network analysis approaches i.e., dynamic residue network (DRN) analysis to decipher drug resistance mechanisms in tuberculosis (TB). This involved an investigation of the drug resistance mutations in the catalase-peroxidase (KatG) and pyrazinamidase (MtPncA) enzymes which are responsible for activation of TB first-line drugs; Isoniazid (INH) and Pyrazinamide (PZA), respectively. In the case of KatG, eleven high confidence (HC) KatG mutations associated with a high prevalence of phenotypic INH resistance were identified and their 3D structures modeled before subjecting them to MD simulations. Global analysis showed an unstable KatG structure and active site environment in the mutants compared to the wildtype. Active site dynamics in the mutants compromised cofactor (heme) interactions resulting in less bonds/interactions compared to the wildtype. Given the importance of the heme, reduced interactions affect enzyme function. Trajectory analysis also showed asymmetric protomer behavior both in the wildtype and mutant systems. DRN analysis identified the KatG dimerization domain and C-terminal domain as functionally important and influential in the enzyme function as per betweenness centrality and eigenvector centrality distribution. In the case of the MtPncA enzyme, our main focus was on understanding the MtPncA binding ability of Nicotinamide (an analogue of PZA) in comparison to PZA, especially in the presence of 82 resistance conferring MtPncA mutations. Like in KatG, the mutant structures were modeled and subjected to MD simulations and analysis. Interestingly, more MtPncA mutants favored NAM interactions compared to PZA i.e., 34 MtPncA mutants steadily coordinated NAM compared to 21 in the case of PZA. Trajectory and ligand interaction analysis showed how increased active site lid loop dynamics affect the NAM binding, especially in the systems with the active site mutations i.e., H51Y, W68R, C72R, L82R, K96N, L159N, and L159R. This led to fewer protein-ligand interactions and eventually ligand ejection. Network analysis further identified the protein core, metal binding site (MBS), and substrate binding site as the most important regions of the enzyme. Furthermore, the degree of centrality analysis showed how specific MtPncA mutations i.e., C14H, F17D, and T412P, interrupt intra-protein communication from the MtPncA core to the MBS, affecting enzyme activity. The analysis of KatG and MtPncA enzyme mutations not only identified the effects of mutations on enzyme behaviour and communication, but also established a framework of computational approaches that can be used for mutational studies in any protein. Besides AMR, the continued encroachment of wildlife habitats due to population growth has exposed humans to wildlife pathogens leading to zoonotic diseases, a recent example being coronavirus disease 2019 (COVID-19). In the second part of the thesis, the established computational approaches in Part 1, were employed to investigate the changes in inter-protein interactions and communication patterns between the severe acute respiratory coronavirus 2 (SARS-CoV-2) with the human host receptor protein (ACE2: angiotensin-converting enzyme 2) consequent to mutations in the SARS-CoV-2 receptor binding domain (RBD). Here, the focus was on RBD mutations of the Omicron sub-lineages. We identified four Omicron-sub lineages with RBD mutations i.e., BA.1, BA.2, BA.3 and BA.4. Each sub-lineage mutations were modeled into RBD structure in complex with the hACE2. MD analysis of the RBD-hACE2 complex highlighted how the RBD mutations change the conformational flexibility of both the RBD and hACE2 compared to the wildtype (WT). Furthermore, DRN analysis identified novel allosteric paths composed of residues with high betweenness and eigenvector centralities linking the RBD to the hACE2 in both the wildtype and mutant systems. Interestingly, these paths were modified with the progression of Omicron sub-lineages, highlighting how the virus evolution affects protein interaction. Lastly, the effect of mutations on S RBD and hACE2 interaction was investigated from the hACE2 perspective by focusing on mutations in the hACE2 protein. Here, naturally occurring hACE2 polymorphisms in African populations i.e., S19P, K26R, M82I, K341R, N546D, and D597Q, were identified and their effects on RBD-hACE2 interactions investigated in presence of the Omicron BA.4/5 RBD mutations. The hACE2 polymorphisms subtly affected the complex dynamics; however, RBD-hACE2 interaction analysis showed that hACE2 mutations effect the complex formation and interaction. Here, the K26R mutation favored RBD-hACE2 interactions, whereas S19P resulted in fewer inter-protein interactions than the reference system. The M82I mutation resulted in a higher RBD-hACE2 binding energy compared to the wildtype meaning that the mutation might not favor RBD binding to the hACE2. On the other hand, K341R had the most RBD-hACE2 interactions suggesting that it probably favors RBD binding to the hACE2. N546D and D597Q had diminutive differences to the reference system. Interestingly, the network of high betweenness centrality residues linking the two proteins, as seen in the previous paragraph, were maintained/modified in presence of hACE2 mutations. HACE2 mutations also changed the enzyme network patterns resulting in a concentration of high eigenvector centrality residues around the zinc-binding and active site region, ultimately influencing the enzyme functionality. Altogether, the thesis highlights fundamental structural and network changes consequent to mutations both in TB and COVID-19 proteins of interest using in silico approaches. These approaches not only provide a new context on impact of mutations in TB and COVID target proteins, but also presents a framework that be implemented in other protein mutation studies. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2023
- Full Text:
- Authors: Barozi, Victor
- Date: 2023-10-13
- Subjects: Microbial mutation , COVID-19 (Disease) , Drug resistance in microorganisms , Antitubercular agents , Tuberculosis , Molecular dynamics , Single nucleotide polymorphisms
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/431626 , vital:72791 , DOI 10.21504/10962/431626
- Description: One of the greatest challenges facing modern medicine and the global public health today is antimicrobial drug resistance (AMR). This “silent pandemic,” as coined by the world health organization (WHO), is steadily increasing with an estimated 4.95 million mortalities attributed to AMR in 2019, 1.27 million of which were directly linked to AMR. Some of the contributors to AMR include self-prescription, drug overuse, sub-optimal drug prescriptions by health workers, and inaccessibility to drugs, especially in remote areas, which leads to poor adherence. The situation is aggravated by the upsurge of new zoonotic infections like the coronavirus disease 2019, which present unique challenges and take the bulk of resources hence stunting the fight against AMR. Quite alarming still is our current antimicrobial arsenal, which hasn’t had any novel antimicrobial drug discovery/addition, of a new class, since the 1980s. This puts a burden on the existing broad-spectrum antimicrobial drugs which are already struggling against multi-drug resistant strains like multi-drug resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB). Besides the search for new antimicrobial agents, the other avenue for addressing AMR is studying drug resistance mechanisms, especially single nucleotide polymorphisms (SNPs), that change drug target characteristics. With the advancement of computational power and data storage resources, computational approaches can be applied in mutational studies to provide insight into the drug resistance mechanisms with an aim to inform future drug design and development. Therefore, in the first part of this thesis, we employ integrative in silico approaches, including 3D structure modeling, molecular dynamic (MD) simulations, comparative essential dynamics (ED), and protein network analysis approaches i.e., dynamic residue network (DRN) analysis to decipher drug resistance mechanisms in tuberculosis (TB). This involved an investigation of the drug resistance mutations in the catalase-peroxidase (KatG) and pyrazinamidase (MtPncA) enzymes which are responsible for activation of TB first-line drugs; Isoniazid (INH) and Pyrazinamide (PZA), respectively. In the case of KatG, eleven high confidence (HC) KatG mutations associated with a high prevalence of phenotypic INH resistance were identified and their 3D structures modeled before subjecting them to MD simulations. Global analysis showed an unstable KatG structure and active site environment in the mutants compared to the wildtype. Active site dynamics in the mutants compromised cofactor (heme) interactions resulting in less bonds/interactions compared to the wildtype. Given the importance of the heme, reduced interactions affect enzyme function. Trajectory analysis also showed asymmetric protomer behavior both in the wildtype and mutant systems. DRN analysis identified the KatG dimerization domain and C-terminal domain as functionally important and influential in the enzyme function as per betweenness centrality and eigenvector centrality distribution. In the case of the MtPncA enzyme, our main focus was on understanding the MtPncA binding ability of Nicotinamide (an analogue of PZA) in comparison to PZA, especially in the presence of 82 resistance conferring MtPncA mutations. Like in KatG, the mutant structures were modeled and subjected to MD simulations and analysis. Interestingly, more MtPncA mutants favored NAM interactions compared to PZA i.e., 34 MtPncA mutants steadily coordinated NAM compared to 21 in the case of PZA. Trajectory and ligand interaction analysis showed how increased active site lid loop dynamics affect the NAM binding, especially in the systems with the active site mutations i.e., H51Y, W68R, C72R, L82R, K96N, L159N, and L159R. This led to fewer protein-ligand interactions and eventually ligand ejection. Network analysis further identified the protein core, metal binding site (MBS), and substrate binding site as the most important regions of the enzyme. Furthermore, the degree of centrality analysis showed how specific MtPncA mutations i.e., C14H, F17D, and T412P, interrupt intra-protein communication from the MtPncA core to the MBS, affecting enzyme activity. The analysis of KatG and MtPncA enzyme mutations not only identified the effects of mutations on enzyme behaviour and communication, but also established a framework of computational approaches that can be used for mutational studies in any protein. Besides AMR, the continued encroachment of wildlife habitats due to population growth has exposed humans to wildlife pathogens leading to zoonotic diseases, a recent example being coronavirus disease 2019 (COVID-19). In the second part of the thesis, the established computational approaches in Part 1, were employed to investigate the changes in inter-protein interactions and communication patterns between the severe acute respiratory coronavirus 2 (SARS-CoV-2) with the human host receptor protein (ACE2: angiotensin-converting enzyme 2) consequent to mutations in the SARS-CoV-2 receptor binding domain (RBD). Here, the focus was on RBD mutations of the Omicron sub-lineages. We identified four Omicron-sub lineages with RBD mutations i.e., BA.1, BA.2, BA.3 and BA.4. Each sub-lineage mutations were modeled into RBD structure in complex with the hACE2. MD analysis of the RBD-hACE2 complex highlighted how the RBD mutations change the conformational flexibility of both the RBD and hACE2 compared to the wildtype (WT). Furthermore, DRN analysis identified novel allosteric paths composed of residues with high betweenness and eigenvector centralities linking the RBD to the hACE2 in both the wildtype and mutant systems. Interestingly, these paths were modified with the progression of Omicron sub-lineages, highlighting how the virus evolution affects protein interaction. Lastly, the effect of mutations on S RBD and hACE2 interaction was investigated from the hACE2 perspective by focusing on mutations in the hACE2 protein. Here, naturally occurring hACE2 polymorphisms in African populations i.e., S19P, K26R, M82I, K341R, N546D, and D597Q, were identified and their effects on RBD-hACE2 interactions investigated in presence of the Omicron BA.4/5 RBD mutations. The hACE2 polymorphisms subtly affected the complex dynamics; however, RBD-hACE2 interaction analysis showed that hACE2 mutations effect the complex formation and interaction. Here, the K26R mutation favored RBD-hACE2 interactions, whereas S19P resulted in fewer inter-protein interactions than the reference system. The M82I mutation resulted in a higher RBD-hACE2 binding energy compared to the wildtype meaning that the mutation might not favor RBD binding to the hACE2. On the other hand, K341R had the most RBD-hACE2 interactions suggesting that it probably favors RBD binding to the hACE2. N546D and D597Q had diminutive differences to the reference system. Interestingly, the network of high betweenness centrality residues linking the two proteins, as seen in the previous paragraph, were maintained/modified in presence of hACE2 mutations. HACE2 mutations also changed the enzyme network patterns resulting in a concentration of high eigenvector centrality residues around the zinc-binding and active site region, ultimately influencing the enzyme functionality. Altogether, the thesis highlights fundamental structural and network changes consequent to mutations both in TB and COVID-19 proteins of interest using in silico approaches. These approaches not only provide a new context on impact of mutations in TB and COVID target proteins, but also presents a framework that be implemented in other protein mutation studies. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2023
- Full Text:
In-silico investigation of the effects of genetic mutations on the structural dynamics of thiopurine s-methyltransferase and their implications on the metabolism of 6-mercaptopurine
- Authors: Mwaniki, Rehema Mukami
- Date: 2023-10-13
- Subjects: Mutation , Thiopurine S-methyltransferase , Mercaptopurine , Molecular dynamics , Protein structure , Structural dynamics
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/432553 , vital:72880
- Description: Thiopurine S-methyltransferase (TPMT) is a cytosolic enzyme that catalyzes the S-methylation of aromatic and heterocyclic sulfhydryl compounds such as 6-mercaptopurine (6MP), 6-thioguanine (6TG) and azathioprine (AZA) which is first converted to 6MP through reduction by glutathione S- transferases (GST). The compounds, generally referred to as thiopurines, are immunosuppressants used to treat childhood acute lymphoblastic leukemia (ALL), autoimmune disorders and transplant rejection. Thiopurines are prodrugs which require metabolic activation to give thioguanine nucleotides that exert their cytotoxic effects by incorporation into DNA or inhibiting purine synthesis. The methylation reaction by TPMT utilizing S-adenosylmethionine (SAM) as the methyl donor prevents their conversion to these toxic compounds. The catalytic activity of TPMT in metabolising these compounds has been associated with occurrence of genetic variations. The variations that result to missense mutations cause amino-acid changes and in turn alter the polypeptide sequence of the protein. This could alter functionality and structural dynamics of the enzyme. This study sought to understand the underlying mechanism by which 7 specially selected mutations impede metabolic activity of the enzyme on 6-MP using in silico techniques. VAPOR and PredictSNP were used to predict the effects of single nucleotide polymorphisms (SNPs) on the stability and function of the enzyme. Of the 7 mutations, only H227Q was predicted to be functionally benign while the rest (L49S, L69V, A80P, R163H, R163C and R163P) were predicted to be deleterious or associated with disease. All the SNPs were predicted to destabilize the enzyme. Molecular dynamics (MD) simulations were preformed to mimic the behaviour of the apo, holo and drug-bound WT and mutant enzymes in vivo. This was followed by post-MD analysis to identify changes in the local and global motions of the protein in the presence of mutations and changes in intra-protein communication networks through contact map and centrality metrics calculations. RMSD and Rg analyses were performed to assess changes in global motions and compactness of the enzyme in the apo, holo and drug-bound states and in the presence of mutations. These revealed that binding of the ligand had a stabilizing effect on the WT enzyme evident from more steady trends from the analyses across trajectories in the holo and drug-bound enzymes compared to the apoenzyme. The occurrence of mutations had an effect on the global motions and compactness of the enzyme across the trajectories. Most mutations resulted in destabilized systems and less compact structures shown by unsteady RMSD and Rg across trajectories respectively. The drugbound systems appeared to be more stable in most of the systems meaning that the binding of 6MP stabilized the enzyme regardless of the presence of a mutation. RMSF analysis recorded local changes in residue flexibility due to the presence of mutations in all the systems. All the drug-bound mutant systems lost flexibility on the αAhelix which caps the active site. This could have an effect on drug binding and result to defective drug metabolism. The A80P mutation resulted to a more rigid structure from both global and local motions compared to the WT enzyme which could be associated with its nearly loss of function in vivo and in vitro. Dynamic cross correlation calculations were performed to assess how the atoms moved together. Correlated, anti-correlated and areas of no correlations were recorded in all the systems and in similar places when compared to each other. This meant that occurrence of mutations had no effect on how the atoms moved together. Contact map analysis showed that occurrence of mutations caused changes in interactions around the positions where the mutations occurred, which could have an effect on protein structural dynamics. The A80P substitution which occurred on the surface away from the binding site was identified as an allosteric mutation that resulted to changes in the catalytic site. Contact maps for the drug-cofactor complex in the mutant systems in comparison with the WT protein revealed changes that could suggest reorientation of the drug at the catalytic site. This could be an implication to altered drug metabolism. Eigenvector centrality (EC) and betweenness centrality (BC) for the most equilibrated portions of the trajectories were calculated for all the studied systems to identify residues connected to the most important residues and those that were spanned the most in shortest paths connecting other residues. Areas that scored highest in these metrics where mostly found in regions surrounding the catalytic site. Top 5% centrality hubs calculations showed loss of major hubs due to mutations with gaining of new ones. This means that mutations affected communication networks within the protein. The gained hubs were in areas close-by the lost ones which could have been an attempt of the protein to accommodate the mutations. Persistent top 5% BC hubs were identified at positions 90 and 151 while one persistent top 5% EC hub was identified at position 70. This positions play important roles in shaping the catalytic site and are in direct contact with the ligands. It was concluded that in silico techniques and analysis applied in this study revealed possible mechanisms in which genetic variations affected the structural dynamics of TMPT enzyme an affecte 6MP metabolism. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2023
- Full Text:
- Authors: Mwaniki, Rehema Mukami
- Date: 2023-10-13
- Subjects: Mutation , Thiopurine S-methyltransferase , Mercaptopurine , Molecular dynamics , Protein structure , Structural dynamics
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/432553 , vital:72880
- Description: Thiopurine S-methyltransferase (TPMT) is a cytosolic enzyme that catalyzes the S-methylation of aromatic and heterocyclic sulfhydryl compounds such as 6-mercaptopurine (6MP), 6-thioguanine (6TG) and azathioprine (AZA) which is first converted to 6MP through reduction by glutathione S- transferases (GST). The compounds, generally referred to as thiopurines, are immunosuppressants used to treat childhood acute lymphoblastic leukemia (ALL), autoimmune disorders and transplant rejection. Thiopurines are prodrugs which require metabolic activation to give thioguanine nucleotides that exert their cytotoxic effects by incorporation into DNA or inhibiting purine synthesis. The methylation reaction by TPMT utilizing S-adenosylmethionine (SAM) as the methyl donor prevents their conversion to these toxic compounds. The catalytic activity of TPMT in metabolising these compounds has been associated with occurrence of genetic variations. The variations that result to missense mutations cause amino-acid changes and in turn alter the polypeptide sequence of the protein. This could alter functionality and structural dynamics of the enzyme. This study sought to understand the underlying mechanism by which 7 specially selected mutations impede metabolic activity of the enzyme on 6-MP using in silico techniques. VAPOR and PredictSNP were used to predict the effects of single nucleotide polymorphisms (SNPs) on the stability and function of the enzyme. Of the 7 mutations, only H227Q was predicted to be functionally benign while the rest (L49S, L69V, A80P, R163H, R163C and R163P) were predicted to be deleterious or associated with disease. All the SNPs were predicted to destabilize the enzyme. Molecular dynamics (MD) simulations were preformed to mimic the behaviour of the apo, holo and drug-bound WT and mutant enzymes in vivo. This was followed by post-MD analysis to identify changes in the local and global motions of the protein in the presence of mutations and changes in intra-protein communication networks through contact map and centrality metrics calculations. RMSD and Rg analyses were performed to assess changes in global motions and compactness of the enzyme in the apo, holo and drug-bound states and in the presence of mutations. These revealed that binding of the ligand had a stabilizing effect on the WT enzyme evident from more steady trends from the analyses across trajectories in the holo and drug-bound enzymes compared to the apoenzyme. The occurrence of mutations had an effect on the global motions and compactness of the enzyme across the trajectories. Most mutations resulted in destabilized systems and less compact structures shown by unsteady RMSD and Rg across trajectories respectively. The drugbound systems appeared to be more stable in most of the systems meaning that the binding of 6MP stabilized the enzyme regardless of the presence of a mutation. RMSF analysis recorded local changes in residue flexibility due to the presence of mutations in all the systems. All the drug-bound mutant systems lost flexibility on the αAhelix which caps the active site. This could have an effect on drug binding and result to defective drug metabolism. The A80P mutation resulted to a more rigid structure from both global and local motions compared to the WT enzyme which could be associated with its nearly loss of function in vivo and in vitro. Dynamic cross correlation calculations were performed to assess how the atoms moved together. Correlated, anti-correlated and areas of no correlations were recorded in all the systems and in similar places when compared to each other. This meant that occurrence of mutations had no effect on how the atoms moved together. Contact map analysis showed that occurrence of mutations caused changes in interactions around the positions where the mutations occurred, which could have an effect on protein structural dynamics. The A80P substitution which occurred on the surface away from the binding site was identified as an allosteric mutation that resulted to changes in the catalytic site. Contact maps for the drug-cofactor complex in the mutant systems in comparison with the WT protein revealed changes that could suggest reorientation of the drug at the catalytic site. This could be an implication to altered drug metabolism. Eigenvector centrality (EC) and betweenness centrality (BC) for the most equilibrated portions of the trajectories were calculated for all the studied systems to identify residues connected to the most important residues and those that were spanned the most in shortest paths connecting other residues. Areas that scored highest in these metrics where mostly found in regions surrounding the catalytic site. Top 5% centrality hubs calculations showed loss of major hubs due to mutations with gaining of new ones. This means that mutations affected communication networks within the protein. The gained hubs were in areas close-by the lost ones which could have been an attempt of the protein to accommodate the mutations. Persistent top 5% BC hubs were identified at positions 90 and 151 while one persistent top 5% EC hub was identified at position 70. This positions play important roles in shaping the catalytic site and are in direct contact with the ligands. It was concluded that in silico techniques and analysis applied in this study revealed possible mechanisms in which genetic variations affected the structural dynamics of TMPT enzyme an affecte 6MP metabolism. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2023
- Full Text:
Bioinformatics tool and web server development focusing on structural bioinformatics applications
- Authors: Nabatanzi, Margaret
- Date: 2022-10-14
- Subjects: Structural bioinformatics , Proteins Structure , Protein structure prediction , Proteins Conformation , Protein complex
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/365700 , vital:65777 , DOI https://doi.org/10.21504/10962/365700
- Description: This thesis is divided into two main sections: Part 1 describes the design, and evaluation of the accuracy of a new web server – PRotein Interactive MOdeling (PRIMO-Complexes) for modeling protein complexes and biological assemblies. The second part describes the development of bioinformatics tools to predict HIV-1 drug resistance and support bioinformatics research and education. Recent technological advances have resulted in a tremendous increase in the number of sequences and protein structures deposited in the Universal Protein Resource Knowledgebase (UniProtKB) and the Protein Data Bank (PDB). However, the number of sequences has increased at a higher rate compared with the experimentally solved multimeric protein structures. This is partly due to advances in high-throughput sequencing technology. To fill this protein sequence-structure gap, computational approaches have been developed to predict protein structures from available sequences. Computational approaches include template-based and ab initio modeling with the former being the most reliable. Template-based modeling process can be achieved using either standalone software or automated modeling web servers. However, using standalone software requires familiarity with command-line interfaces as well as utilising other intermediate programs which could be daunting to novice users. To alleviate some of these problems, the modeling process has been automated, however, it still has numerous challenges. To date, only a few web servers that support multimeric protein modeling have been developed and even these provide little, if any user involvement in the process. To address some of these issues, a new web server – PRIMO-Complexes – was developed to model protein complexes and biological assemblies. The existing PRIMO web server could only model monomeric proteins. Part 1 of this thesis provides a detailed account of the development and evaluation of PRIMO-Complexes. The rationale for developing this new web server was based on the understanding that most proteins function as protein multimers and often the ligand-binding sites, and enzyme active sites are located at the protein-protein interfaces. It, therefore, necessitated developing capabilities for modeling multimeric proteins. PRIMO-Complexes web server was developed using the Waterfall system development life cycle model, is based on the Django web framework and makes use of high-performance computing resources to execute jobs. The accuracy of the algorithms embedded in PRIMO- Complexes was evaluated and the results were promising. Additionally, PRIMO-Complexes performs comparatively well in relation to other web servers that offer multimeric protein modeling. Another unique feature of PRIMO-Complexes is its interactivity. The webserver was developed with capabilities for allowing users to model multimeric proteins with an appreciable degree of control over the process. In the second part of the thesis several other bioinformatics tools are described, for example, a webserver for predicting HIV-1 drug resistance, the RUBi protein model repository, and a bioinformatics web portal for education and research resources. RUBi protein model repository stores verified theoretical models built using various modeling approaches. This enables users to easily access models to reproduce and/or further the research. This is described in chapter 5. Chapter 6 describes the design and development of the Human Immunodeficiency type 1 Resistance Predictor (HIV-1 ResPredictor), a web application that employs artificial neural networks (ANN) to predict drug resistance in patients infected with HIV-1 subtype B. The ANNs and subtype classifiers performed well making this web application potentially useful to both clinicians and researchers in this era of personalised medicine. Finally, chapter 7 describes a bioinformatics education web portal that equips students with information on how to use bioinformatics online resources. Being aware of these resources is not enough without a deeper understanding and guidance on how to apply bioinformatics methods to solve practical problems. This web portal was aimed at familiarising students with the basic terminology and approaches in structural bioinformatics. Students will potentially gain skills to conduct real-life bioinformatics research to obtain biological insights. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
- Authors: Nabatanzi, Margaret
- Date: 2022-10-14
- Subjects: Structural bioinformatics , Proteins Structure , Protein structure prediction , Proteins Conformation , Protein complex
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/365700 , vital:65777 , DOI https://doi.org/10.21504/10962/365700
- Description: This thesis is divided into two main sections: Part 1 describes the design, and evaluation of the accuracy of a new web server – PRotein Interactive MOdeling (PRIMO-Complexes) for modeling protein complexes and biological assemblies. The second part describes the development of bioinformatics tools to predict HIV-1 drug resistance and support bioinformatics research and education. Recent technological advances have resulted in a tremendous increase in the number of sequences and protein structures deposited in the Universal Protein Resource Knowledgebase (UniProtKB) and the Protein Data Bank (PDB). However, the number of sequences has increased at a higher rate compared with the experimentally solved multimeric protein structures. This is partly due to advances in high-throughput sequencing technology. To fill this protein sequence-structure gap, computational approaches have been developed to predict protein structures from available sequences. Computational approaches include template-based and ab initio modeling with the former being the most reliable. Template-based modeling process can be achieved using either standalone software or automated modeling web servers. However, using standalone software requires familiarity with command-line interfaces as well as utilising other intermediate programs which could be daunting to novice users. To alleviate some of these problems, the modeling process has been automated, however, it still has numerous challenges. To date, only a few web servers that support multimeric protein modeling have been developed and even these provide little, if any user involvement in the process. To address some of these issues, a new web server – PRIMO-Complexes – was developed to model protein complexes and biological assemblies. The existing PRIMO web server could only model monomeric proteins. Part 1 of this thesis provides a detailed account of the development and evaluation of PRIMO-Complexes. The rationale for developing this new web server was based on the understanding that most proteins function as protein multimers and often the ligand-binding sites, and enzyme active sites are located at the protein-protein interfaces. It, therefore, necessitated developing capabilities for modeling multimeric proteins. PRIMO-Complexes web server was developed using the Waterfall system development life cycle model, is based on the Django web framework and makes use of high-performance computing resources to execute jobs. The accuracy of the algorithms embedded in PRIMO- Complexes was evaluated and the results were promising. Additionally, PRIMO-Complexes performs comparatively well in relation to other web servers that offer multimeric protein modeling. Another unique feature of PRIMO-Complexes is its interactivity. The webserver was developed with capabilities for allowing users to model multimeric proteins with an appreciable degree of control over the process. In the second part of the thesis several other bioinformatics tools are described, for example, a webserver for predicting HIV-1 drug resistance, the RUBi protein model repository, and a bioinformatics web portal for education and research resources. RUBi protein model repository stores verified theoretical models built using various modeling approaches. This enables users to easily access models to reproduce and/or further the research. This is described in chapter 5. Chapter 6 describes the design and development of the Human Immunodeficiency type 1 Resistance Predictor (HIV-1 ResPredictor), a web application that employs artificial neural networks (ANN) to predict drug resistance in patients infected with HIV-1 subtype B. The ANNs and subtype classifiers performed well making this web application potentially useful to both clinicians and researchers in this era of personalised medicine. Finally, chapter 7 describes a bioinformatics education web portal that equips students with information on how to use bioinformatics online resources. Being aware of these resources is not enough without a deeper understanding and guidance on how to apply bioinformatics methods to solve practical problems. This web portal was aimed at familiarising students with the basic terminology and approaches in structural bioinformatics. Students will potentially gain skills to conduct real-life bioinformatics research to obtain biological insights. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
Identification of novel compounds against Plasmodium falciparum Cytochrome bc1 Complex inhibiting the trans-membrane electron transfer pathway: an In Silico study
- Authors: Chebon, Lorna Jemosop
- Date: 2022-10-14
- Subjects: Malaria , Plasmodium falciparum , Molecular dynamics , Antimalarials , Molecules Models , Docking , Cytochromes , Drug resistance , Computer simulation , Drugs Computer-aided design , System analysis
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/365666 , vital:65774 , DOI https://doi.org/10.21504/10962/365666
- Description: Malaria continues to be a burden globally with a myriad of challenges deterring eradication efforts. With most antimalarials facing drug resistance, such as atovaquone (ATQ), alternative compounds that can withstand resistance are warranted. The Plasmodium falciparum cytochrome b (PfCytb), a subunit of P. falciparum cytochrome bc1 complex, is a validated drug target. Structurally, cytochrome b, cytochrome c1, and iron sulphur protein (ISP) subunits form the catalytic domain of the protein complex having heme bL, heme bH and iron-sulphur [2FE-2S] cluster cofactors. These cofactos have redox centres to aid in the electron transfer (ET) process. These subunits promote ET mainly through the enzyme’s ubiquinol oxidation (Qo) and ubiquinone reduction (Qi) processes in the catalytic domain. ATQ drug has been used in the prevention and treatment of uncomplicated malaria by targeting PfCytb protein. Once the mitochondrial transmembrane ET pathway is inhibited, it causes a collapse in its membrane potential. Previously reported ATQ drug resistance has been associated with the point mutations Y268C, Y268N and Y268S. Thus, in finding alternatives to the ATQ drug, this research aimed to: i) employ in silico approaches incorporating protein into phospholipid bilayer for the first time to understand the parasites’ resistance mechanism; ii) determine any sequence and structural differences that could be explored in drug design studies; and iii) screen for PfCytb-iron sulphur protein (Cytb-ISP) hit compounds from South African natural compound database (SANCDB) and Medicines for Malaria Venture (MMV) that can withstand the identified mutations. Using computational tools, comparative sequence and structural analyses were performed on the cytochrome b protein, where the ultimate focus was on P. falciparum cytochrome b and its human homolog. Through multiple sequence alignment, motif discovery and phylogeny, differences between P. falciparum and H. sapiens cytochrome b were identified. Protein modelling of both P. falciparum and H. sapiens cytochrome b - iron sulphur protein (PfCytb-ISP and HsCytb-ISP) was performed. Results showed that at the sequence level, there were few amino acid residue differences because the protein is highly conserved. Important to note is the four-residue deletion in Plasmodium spp. absent in the human homolog. Motif analysis discovered five unique motifs in P. falciparum cytochrome b protein which were mapped onto the predicted protein model. These motifs were not in regions of functional importance; hence their function is still unknown. At a structural level, the four-residue deletion was observed to alter the Qo substrate binding pocket as reported in previous studies and confirmed in this study. This deletion resulted in a 0.83 Å structural displacement. Also, there are currently no in silico studies that have performed experiments with P. falciparum cytochrome b protein incorporated into a phospholipid bilayer. Using 350 ns molecular dynamics (MD) simulations of the holo and ATQ-bound systems, the study highlighted the resistance mechanism of the parasite protein where the loss of active site residue-residue interactions was identified, all linked to the three mutations. The identified compromised interactions are likely to destabilise the protein’s function, specifically in the Qo substrate binding site. This showed the possible effect of mutations on ATQ drug activity, where all three mutations were reported to share a similar resistance mechanism. Thereafter, this research work utilised in silico approaches where both Qo active site and interface pocket were targeted by screening the South African natural compounds database (SANCDB) and Medicines for Malaria Venture (MMV) compounds to identify novel selective hits. SANCDB compounds are known for their structural complexity that preserves the potency of the drug molecule. Both SANCDB and MMV compounds have not been explored as inhibitors against the PfCytb drug target. Molecular docking, molecular dynamics (MD) simulations, principal component, and dynamic residue network (DRN; global and local) analyses were utilised to identify and confirm the potential selective inhibitors. Docking results identified compounds that bound selectively onto PfCytb-ISP with a binding energy ≤ -8.7 kcal/mol-1. Further, this work validated a total of eight potential selective compounds to inhibit PfCytb-ISP protein (Qo active site) not only in the wild-type but also in the presence of the point mutations Y268C, Y268N and Y268S. The selective binding of these hit compounds could be linked to the differences reported at sequence/residue level in chapter 3. DRN and residue contact map analyses of the eight compounds in holo and ligand-bound systems revealed reduced residue interactions and decreased protein communication. This suggests that the eight compounds show the possibility of inhibiting the parasite and disrupting important residue-residue interactions. Additionally, 13 selective compounds were identified to bind at the protein’s heterodimer interface, where global and local analysis confirmed their effect on active site residues (distal location) as well as on the communication network. Based on the sequence differences between PfCytb and the human homolog, these findings suggest these selective compounds as potential allosteric modulators of the parasite enzyme, which may serve as possible replacements of the already resistant ATQ drug. Therefore, these findings pave the way for further in vitro studies to establish their anti-plasmodial inhibition levels. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
- Authors: Chebon, Lorna Jemosop
- Date: 2022-10-14
- Subjects: Malaria , Plasmodium falciparum , Molecular dynamics , Antimalarials , Molecules Models , Docking , Cytochromes , Drug resistance , Computer simulation , Drugs Computer-aided design , System analysis
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/365666 , vital:65774 , DOI https://doi.org/10.21504/10962/365666
- Description: Malaria continues to be a burden globally with a myriad of challenges deterring eradication efforts. With most antimalarials facing drug resistance, such as atovaquone (ATQ), alternative compounds that can withstand resistance are warranted. The Plasmodium falciparum cytochrome b (PfCytb), a subunit of P. falciparum cytochrome bc1 complex, is a validated drug target. Structurally, cytochrome b, cytochrome c1, and iron sulphur protein (ISP) subunits form the catalytic domain of the protein complex having heme bL, heme bH and iron-sulphur [2FE-2S] cluster cofactors. These cofactos have redox centres to aid in the electron transfer (ET) process. These subunits promote ET mainly through the enzyme’s ubiquinol oxidation (Qo) and ubiquinone reduction (Qi) processes in the catalytic domain. ATQ drug has been used in the prevention and treatment of uncomplicated malaria by targeting PfCytb protein. Once the mitochondrial transmembrane ET pathway is inhibited, it causes a collapse in its membrane potential. Previously reported ATQ drug resistance has been associated with the point mutations Y268C, Y268N and Y268S. Thus, in finding alternatives to the ATQ drug, this research aimed to: i) employ in silico approaches incorporating protein into phospholipid bilayer for the first time to understand the parasites’ resistance mechanism; ii) determine any sequence and structural differences that could be explored in drug design studies; and iii) screen for PfCytb-iron sulphur protein (Cytb-ISP) hit compounds from South African natural compound database (SANCDB) and Medicines for Malaria Venture (MMV) that can withstand the identified mutations. Using computational tools, comparative sequence and structural analyses were performed on the cytochrome b protein, where the ultimate focus was on P. falciparum cytochrome b and its human homolog. Through multiple sequence alignment, motif discovery and phylogeny, differences between P. falciparum and H. sapiens cytochrome b were identified. Protein modelling of both P. falciparum and H. sapiens cytochrome b - iron sulphur protein (PfCytb-ISP and HsCytb-ISP) was performed. Results showed that at the sequence level, there were few amino acid residue differences because the protein is highly conserved. Important to note is the four-residue deletion in Plasmodium spp. absent in the human homolog. Motif analysis discovered five unique motifs in P. falciparum cytochrome b protein which were mapped onto the predicted protein model. These motifs were not in regions of functional importance; hence their function is still unknown. At a structural level, the four-residue deletion was observed to alter the Qo substrate binding pocket as reported in previous studies and confirmed in this study. This deletion resulted in a 0.83 Å structural displacement. Also, there are currently no in silico studies that have performed experiments with P. falciparum cytochrome b protein incorporated into a phospholipid bilayer. Using 350 ns molecular dynamics (MD) simulations of the holo and ATQ-bound systems, the study highlighted the resistance mechanism of the parasite protein where the loss of active site residue-residue interactions was identified, all linked to the three mutations. The identified compromised interactions are likely to destabilise the protein’s function, specifically in the Qo substrate binding site. This showed the possible effect of mutations on ATQ drug activity, where all three mutations were reported to share a similar resistance mechanism. Thereafter, this research work utilised in silico approaches where both Qo active site and interface pocket were targeted by screening the South African natural compounds database (SANCDB) and Medicines for Malaria Venture (MMV) compounds to identify novel selective hits. SANCDB compounds are known for their structural complexity that preserves the potency of the drug molecule. Both SANCDB and MMV compounds have not been explored as inhibitors against the PfCytb drug target. Molecular docking, molecular dynamics (MD) simulations, principal component, and dynamic residue network (DRN; global and local) analyses were utilised to identify and confirm the potential selective inhibitors. Docking results identified compounds that bound selectively onto PfCytb-ISP with a binding energy ≤ -8.7 kcal/mol-1. Further, this work validated a total of eight potential selective compounds to inhibit PfCytb-ISP protein (Qo active site) not only in the wild-type but also in the presence of the point mutations Y268C, Y268N and Y268S. The selective binding of these hit compounds could be linked to the differences reported at sequence/residue level in chapter 3. DRN and residue contact map analyses of the eight compounds in holo and ligand-bound systems revealed reduced residue interactions and decreased protein communication. This suggests that the eight compounds show the possibility of inhibiting the parasite and disrupting important residue-residue interactions. Additionally, 13 selective compounds were identified to bind at the protein’s heterodimer interface, where global and local analysis confirmed their effect on active site residues (distal location) as well as on the communication network. Based on the sequence differences between PfCytb and the human homolog, these findings suggest these selective compounds as potential allosteric modulators of the parasite enzyme, which may serve as possible replacements of the already resistant ATQ drug. Therefore, these findings pave the way for further in vitro studies to establish their anti-plasmodial inhibition levels. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
Identification of selective novel hits against Mycobacterium tuberculosis KasA potential allosteric sites using bioinformatics approaches
- Authors: Hare, Fadzayi Faith
- Date: 2022-10-14
- Subjects: Tuberculosis , Docking , Molecules Models , Virtual screening , Multidrug-resistant tuberculosis , Fatty acids Synthesis , Drugs Design
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/362842 , vital:65367
- Description: Tuberculosis (TB) is a global health threat that has led to approximately 1.5 million deaths annually. According to the World Health Organization (WHO), TB is among the top ten deadly diseases and is the leading cause of death due to a single infectious agent. The main challenge in the effective treatment and control of TB is the ongoing emergence of resistant strains of Mycobacterium tuberculosis (Mtb) which lead to multi-drug resistant (MDR) and extensive-drug resistant (XDR) TB. Hence, the identification and characterization of novel drug targets and drugs that modulate the activity of the pathogen are an urgent priority. The current situation even necessitates the reengineering or repurposing of drugs in order to achieve effective control. The β-ketoacyl-acyl carrier protein synthase I (KasA) of Mycobacterium tuberculosis is an essential enzyme in the mycobacterial fatty acid synthesis (FAS-II) pathway and is believed to be a promising target for drug discovery in TB. It is one of the five main proteins of the FAS-II pathway and catalyzes a key condensation reaction in the synthesis of meromycolate chains, the precursors of mycolic acids involved in cell wall formation. Although this protein has been extensively studied, little research has been devoted to the allosteric inhibition of potential drug compounds. The main aim of this research was to identify the allosteric sites on the protein that could be involved in the inhibition of substrate binding activities and novel drug compounds that bind to these sites by use of in-silico approaches. The bioinformatics approaches used in this study were divided into four main objectives namely identification of KasA homolog sequences, sequence analysis and protein characterization, allosteric site search and lastly virtual screening of DrugBank compounds via molecular docking. Fifteen homolog sequences were identified from the BLASTP analysis and were derived from bacteria, fungi and mammals. In order to discover important residues and regions within the KasA proteins, sequence alignment, motif analysis and phylogenetic studies were performed using Mtb KasA as a reference. Sequence alignment revealed conserved residues in all KasA proteins that have functional importance such as the catalytic triad residues (Cys171, His311 and His345). Motif analysis identified 18 highly conserved motifs within the KasA proteins with structural and functional roles. In addition, motifs unique to the Mtb KasA protein were also identified and explored for inhibitor drug design purposes. Phylogenetic analysis of the homolog sequences showed a distinct clustering of prokaryotes and eukaryotes. A distinctive clustering was also observed for species belonging to the same genus. Since the mechanism of action of most drugs involves the active site, allosteric site search was conducted on Mtb KasA and the human homolog protein using a combination of pocket detection algorithms with the aim of identifying sites that could be utilized in allosteric modulator drug discovery. This was followed by the virtual screening of 2089 FDA approved DrugBank compounds against the entire protein surfaces of Mtb KasA and Hsmt KasA, performed via molecular docking using AutoDock Vina. Screening of the compounds was based on the binding energies, with more focus on identifying ligands that bound exclusively to the acyl-binding tunnel of Mtb KasA. This reduced the data set to 27 promising drug compounds with a relatively high binding affinity for Mtb KasA, however, further experiments need to be performed to validate this result. Among these compounds were DB08889, DB06755, DB09270, DB11226, DB00392, DB12278, DB08936, DB00781, DB13720 and DB00392, which displayed relatively low binding energies for Mtb KasA when compared to the human homolog protein. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
- Authors: Hare, Fadzayi Faith
- Date: 2022-10-14
- Subjects: Tuberculosis , Docking , Molecules Models , Virtual screening , Multidrug-resistant tuberculosis , Fatty acids Synthesis , Drugs Design
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/362842 , vital:65367
- Description: Tuberculosis (TB) is a global health threat that has led to approximately 1.5 million deaths annually. According to the World Health Organization (WHO), TB is among the top ten deadly diseases and is the leading cause of death due to a single infectious agent. The main challenge in the effective treatment and control of TB is the ongoing emergence of resistant strains of Mycobacterium tuberculosis (Mtb) which lead to multi-drug resistant (MDR) and extensive-drug resistant (XDR) TB. Hence, the identification and characterization of novel drug targets and drugs that modulate the activity of the pathogen are an urgent priority. The current situation even necessitates the reengineering or repurposing of drugs in order to achieve effective control. The β-ketoacyl-acyl carrier protein synthase I (KasA) of Mycobacterium tuberculosis is an essential enzyme in the mycobacterial fatty acid synthesis (FAS-II) pathway and is believed to be a promising target for drug discovery in TB. It is one of the five main proteins of the FAS-II pathway and catalyzes a key condensation reaction in the synthesis of meromycolate chains, the precursors of mycolic acids involved in cell wall formation. Although this protein has been extensively studied, little research has been devoted to the allosteric inhibition of potential drug compounds. The main aim of this research was to identify the allosteric sites on the protein that could be involved in the inhibition of substrate binding activities and novel drug compounds that bind to these sites by use of in-silico approaches. The bioinformatics approaches used in this study were divided into four main objectives namely identification of KasA homolog sequences, sequence analysis and protein characterization, allosteric site search and lastly virtual screening of DrugBank compounds via molecular docking. Fifteen homolog sequences were identified from the BLASTP analysis and were derived from bacteria, fungi and mammals. In order to discover important residues and regions within the KasA proteins, sequence alignment, motif analysis and phylogenetic studies were performed using Mtb KasA as a reference. Sequence alignment revealed conserved residues in all KasA proteins that have functional importance such as the catalytic triad residues (Cys171, His311 and His345). Motif analysis identified 18 highly conserved motifs within the KasA proteins with structural and functional roles. In addition, motifs unique to the Mtb KasA protein were also identified and explored for inhibitor drug design purposes. Phylogenetic analysis of the homolog sequences showed a distinct clustering of prokaryotes and eukaryotes. A distinctive clustering was also observed for species belonging to the same genus. Since the mechanism of action of most drugs involves the active site, allosteric site search was conducted on Mtb KasA and the human homolog protein using a combination of pocket detection algorithms with the aim of identifying sites that could be utilized in allosteric modulator drug discovery. This was followed by the virtual screening of 2089 FDA approved DrugBank compounds against the entire protein surfaces of Mtb KasA and Hsmt KasA, performed via molecular docking using AutoDock Vina. Screening of the compounds was based on the binding energies, with more focus on identifying ligands that bound exclusively to the acyl-binding tunnel of Mtb KasA. This reduced the data set to 27 promising drug compounds with a relatively high binding affinity for Mtb KasA, however, further experiments need to be performed to validate this result. Among these compounds were DB08889, DB06755, DB09270, DB11226, DB00392, DB12278, DB08936, DB00781, DB13720 and DB00392, which displayed relatively low binding energies for Mtb KasA when compared to the human homolog protein. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
Sequence, structure, dynamics, and substrate specificity analyses of bacterial Glycoside Hydrolase 1 enzymes from several activities
- Authors: Veldman, Wayde Michael
- Date: 2022-04-08
- Subjects: Glycosidases , Bioinformatics , Molecular dynamics , Ligands (Biochemistry) , Enzymes , Ligand binding (Biochemistry) , Sequence alignment (Bioinformatics) , Structural bioinformatics
- Language: English
- Type: Doctoral thesis , text
- Identifier: http://hdl.handle.net/10962/233805 , vital:50129 , DOI 10.21504/10962/233810
- Description: Glycoside hydrolase 1 (GH1) enzymes are a ubiquitous family of enzymes that hydrolyse the glycosidic bond between two or more carbohydrates, or between a carbohydrate and a non-carbohydrate moiety. Despite their conserved catalytic domain, these enzymes have many different enzyme activities and/or substrate specificities as a change of only a few residues in the active site can alter their function. Most GH1 active site residues are situated in loop regions, and it is known that enzymes are more likely to develop new functions (broad specificity) if they possess an active site with a high proportion of loops. Furthermore, the GH1 active site consists of several subsites and cooperative binding makes the binding affinity of sites difficult to measure because the properties of one subsite are influenced by the binding of the other subsites. Extensive knowledge of protein-ligand interactions is critical to the comprehension of biology at the molecular level. However, the structural determinants and molecular details of GH1 ligand specificity and affinity are very broad, highly complex, not well understood, and therefore still need to be clarified. The aim of this study was to computationally characterise the activity of three newly solved GH1 crystallographic structures sent to us by our collaborators, and to provide evidence for their ligand-binding specificities. In addition, the differences in structural and biochemical contributions to enzyme specificity and/or function between different GH1 activities/enzymes was assessed, and the sequence/structure/function relationship of several activities of GH1 enzymes was analysed and compared. To accomplish the research aims, sequence analyses involving sequence identity, phylogenetics, and motif discovery were performed. As protein structure is more conserved than sequence, the discovered motifs were mapped to 3D structures for structural analysis and comparisons. To obtain information on enzyme mechanism or mode of action, as well as structure-function relationship, computational methods such as docking, molecular dynamics, binding free energy calculations, and essential dynamics were implemented. These computational approaches can provide information on the active site, binding residues, protein-ligand interactions, binding affinity, conformational change, and most structural or dynamic elements that play a role in enzyme function. The three new structures received from our collaborators are the first GH1 crystallographic structures from Bacillus licheniformis ever determined. As phospho-glycoside compounds were unavailable for purchase for use in activity assays, and as the active sites of the structures were absent of ligand, in silico docking and MD simulations were performed to provide evidence for their GH1 activities and substrate specificities. First though, the amino acid sequences of all known characterised bacterial GH1 enzymes were retrieved from the CAZy database and compared to the sequences of the three new B. licheniformis crystallographic structures which provided evidence of the putative 6Pβ-glucosidase activity of enzyme BlBglH, and dual 6Pβ-glucosidase/6Pβ-galactosidase (dual-phospho) activity of enzymes BlBglB and BlBglC. As all three enzymes were determined to be putative 6Pβ-glycosidase activity enzymes, much of the thesis focused on the overall analysis and comparison of the 6Pβ-glucosidase, 6Pβ-galactosidase, and dual-phospho activities that make up the 6Pβ-glycosidases. The 6Pβ-glycosidase active site residues were identified through consensus of binding interactions using all known 6Pβ-glycosidase PDB structures complexed complete ligand substrates. With regards to the 6Pβ-glucosidase activity, it was found that the L8b loop is longer and forms extra interactions with the L8a loop likely leading to increased L8 loop rigidity which would prevent the displacement of residue Ala423 ensuring a steric clash with galactoconfigured ligands and may engender substrate specificity for gluco-configured ligands only. Also, during molecular dynamics simulations using enzyme BlBglH (6Pβ-glucosidase activity), it was revealed that the favourable binding of substrate stabilises the loops that surround and make up the enzyme active site. Using the BlBglC (dual-phospho activity) enzyme structure with either galacto- (PNP6Pgal) or gluco-configured (PNP6Pglc) ligands, MD simulations in triplicate revealed important details of the broad specificity of dual-phospho activity enzymes. The ligand O4 hydroxyl position is the only difference between PNP6Pgal and PNP6Pgal, and it was found that residues Gln23 and Trp433 bind strongly to the ligand O3 hydroxyl group in the PNP6Pgal-enzyme complex, but to the ligand O4 hydroxyl group in the PNP6Pglc-enzyme complex. Also, His124 formed many hydrogen bonds with the PNP6Pgal O3 hydroxyl group but had none with PNP6Pglc. Alternatively, residues Tyr173, Tyr301, Gln302 and Thr321 formed hydrogen bonds with PNP6Pglc but not PNP6Pgal. Lastly, using multiple 3D structures from various GH1 activities, a large network of conserved interactions between active site residues (and other important residues) was uncovered, which most likely stabilise the loop regions that contain these residues, helping to retain their positions needed for binding molecules. Alternatively, there exists several differing residue-residue interactions when comparing each of the activities which could contribute towards individual activity substrate specificity by causing slightly different overall structure and malleability of the active site. Altogether, the findings in this thesis shed light on the function, mechanisms, dynamics, and ligand-binding of GH1 enzymes – particularly of the 6Pβ-glycosidase activities. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
- Authors: Veldman, Wayde Michael
- Date: 2022-04-08
- Subjects: Glycosidases , Bioinformatics , Molecular dynamics , Ligands (Biochemistry) , Enzymes , Ligand binding (Biochemistry) , Sequence alignment (Bioinformatics) , Structural bioinformatics
- Language: English
- Type: Doctoral thesis , text
- Identifier: http://hdl.handle.net/10962/233805 , vital:50129 , DOI 10.21504/10962/233810
- Description: Glycoside hydrolase 1 (GH1) enzymes are a ubiquitous family of enzymes that hydrolyse the glycosidic bond between two or more carbohydrates, or between a carbohydrate and a non-carbohydrate moiety. Despite their conserved catalytic domain, these enzymes have many different enzyme activities and/or substrate specificities as a change of only a few residues in the active site can alter their function. Most GH1 active site residues are situated in loop regions, and it is known that enzymes are more likely to develop new functions (broad specificity) if they possess an active site with a high proportion of loops. Furthermore, the GH1 active site consists of several subsites and cooperative binding makes the binding affinity of sites difficult to measure because the properties of one subsite are influenced by the binding of the other subsites. Extensive knowledge of protein-ligand interactions is critical to the comprehension of biology at the molecular level. However, the structural determinants and molecular details of GH1 ligand specificity and affinity are very broad, highly complex, not well understood, and therefore still need to be clarified. The aim of this study was to computationally characterise the activity of three newly solved GH1 crystallographic structures sent to us by our collaborators, and to provide evidence for their ligand-binding specificities. In addition, the differences in structural and biochemical contributions to enzyme specificity and/or function between different GH1 activities/enzymes was assessed, and the sequence/structure/function relationship of several activities of GH1 enzymes was analysed and compared. To accomplish the research aims, sequence analyses involving sequence identity, phylogenetics, and motif discovery were performed. As protein structure is more conserved than sequence, the discovered motifs were mapped to 3D structures for structural analysis and comparisons. To obtain information on enzyme mechanism or mode of action, as well as structure-function relationship, computational methods such as docking, molecular dynamics, binding free energy calculations, and essential dynamics were implemented. These computational approaches can provide information on the active site, binding residues, protein-ligand interactions, binding affinity, conformational change, and most structural or dynamic elements that play a role in enzyme function. The three new structures received from our collaborators are the first GH1 crystallographic structures from Bacillus licheniformis ever determined. As phospho-glycoside compounds were unavailable for purchase for use in activity assays, and as the active sites of the structures were absent of ligand, in silico docking and MD simulations were performed to provide evidence for their GH1 activities and substrate specificities. First though, the amino acid sequences of all known characterised bacterial GH1 enzymes were retrieved from the CAZy database and compared to the sequences of the three new B. licheniformis crystallographic structures which provided evidence of the putative 6Pβ-glucosidase activity of enzyme BlBglH, and dual 6Pβ-glucosidase/6Pβ-galactosidase (dual-phospho) activity of enzymes BlBglB and BlBglC. As all three enzymes were determined to be putative 6Pβ-glycosidase activity enzymes, much of the thesis focused on the overall analysis and comparison of the 6Pβ-glucosidase, 6Pβ-galactosidase, and dual-phospho activities that make up the 6Pβ-glycosidases. The 6Pβ-glycosidase active site residues were identified through consensus of binding interactions using all known 6Pβ-glycosidase PDB structures complexed complete ligand substrates. With regards to the 6Pβ-glucosidase activity, it was found that the L8b loop is longer and forms extra interactions with the L8a loop likely leading to increased L8 loop rigidity which would prevent the displacement of residue Ala423 ensuring a steric clash with galactoconfigured ligands and may engender substrate specificity for gluco-configured ligands only. Also, during molecular dynamics simulations using enzyme BlBglH (6Pβ-glucosidase activity), it was revealed that the favourable binding of substrate stabilises the loops that surround and make up the enzyme active site. Using the BlBglC (dual-phospho activity) enzyme structure with either galacto- (PNP6Pgal) or gluco-configured (PNP6Pglc) ligands, MD simulations in triplicate revealed important details of the broad specificity of dual-phospho activity enzymes. The ligand O4 hydroxyl position is the only difference between PNP6Pgal and PNP6Pgal, and it was found that residues Gln23 and Trp433 bind strongly to the ligand O3 hydroxyl group in the PNP6Pgal-enzyme complex, but to the ligand O4 hydroxyl group in the PNP6Pglc-enzyme complex. Also, His124 formed many hydrogen bonds with the PNP6Pgal O3 hydroxyl group but had none with PNP6Pglc. Alternatively, residues Tyr173, Tyr301, Gln302 and Thr321 formed hydrogen bonds with PNP6Pglc but not PNP6Pgal. Lastly, using multiple 3D structures from various GH1 activities, a large network of conserved interactions between active site residues (and other important residues) was uncovered, which most likely stabilise the loop regions that contain these residues, helping to retain their positions needed for binding molecules. Alternatively, there exists several differing residue-residue interactions when comparing each of the activities which could contribute towards individual activity substrate specificity by causing slightly different overall structure and malleability of the active site. Altogether, the findings in this thesis shed light on the function, mechanisms, dynamics, and ligand-binding of GH1 enzymes – particularly of the 6Pβ-glycosidase activities. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
The characterization of GTP Cyclohydrolase I and 6-Pyruvoyl Tetrahydropterin Synthase enzymes as potential anti-malarial drug targets
- Khairallah, Afrah Yousif Huseein
- Authors: Khairallah, Afrah Yousif Huseein
- Date: 2022-04-08
- Subjects: Antimalarials , Plasmodium falciparum , Malaria Chemotherapy , Malaria Africa , Drug resistance , Drug development , Molecular dynamics
- Language: English
- Type: Doctoral thesis , text
- Identifier: http://hdl.handle.net/10962/233784 , vital:50127 , DOI 10.21504/10962/233784
- Description: Malaria remains a public health problem and a high burden of disease, especially in developing countries. The unicellular protozoan malaria parasite of the genus Plasmodium infects about a quarter of a billion people annually, with an estimated 409 000 death cases. The majority of malaria cases occurred in Africa; hence, the region is regarded as endemic for malaria. Global efforts to eradicate the disease led to a decrease in morbidity and mortality rates. However, an enormous burden of malaria infection remains, and it cannot go unnoticed. Countries with limited resources are more affected by the disease, mainly on its public health and socio-economic development, due to many factors besides malaria itself, such as lack of access to adequate, affordable treatments and preventative regimes. Furthermore, the current antimalarial drugs are losing their efficacy because of parasite drug resistance. The emerged drug resistance has reduced the drug efficacy in clearing the parasite from the host system, causing prolonged illness and a higher risk of death. Therefore, the emerged antimalarial drug resistance has hindered the global efforts for malaria control and elimination and established an urgent need for new treatment strategies. When the resistance against classical antimalarial drugs emerged, the class of antifolate antimalarial medicines became the most common alternative. The antifolate antimalarial drugs target the malaria parasite de novo folate biosynthesis pathway by limiting folate derivates, which are essential for the parasite cell growth and survival. Yet again, the malaria parasite developed resistance against the available antifolate drugs, rendering the drugs ineffective in many cases. Given the previous success in targeting the malaria parasite de novo folate biosynthesis pathway, alternative enzymes within this pathway stand as good targets and can be explored to develop new antifolate drugs with novel mechanisms of action. The primary focus of this thesis is to contribute to the existing and growing knowledge of antimalarial drug discovery. The study aims to characterise the malaria parasite de novo folate synthesis pathway enzymes guanosine-5'-triphosphate (GTP) cyclohydrolase I (GCH1) and 6-pyruvoyl tetrahydropterin synthase (PTPS) as alternative drug targets for malaria treatment by using computational approaches. Further, discover new allosteric drug targeting sites within the two enzymes' 3D structures for future drug design and discovery. Sequence and structural analysis were carried out to characterise and pinpoint the two enzymes' unique sequence and structure-based features. From the analyses, key sequence and structure differences were identified between the malaria parasite enzymes relative to their human homolog; the identified sites can aid significantly in designing and developing new antimalarial antifolate drugs with good selectivity toward the parasites’ enzymes. GCH1 and PTPS contain a catalytically essential metal ion in their active site; therefore, force field parameters were needed to study their active sites accurately during all-atom molecular dynamic simulations (MD). The force field parameters were derived through quantum mechanics potential energy surface scans of the metals bonded terms and evaluated via all-atom MD simulations. Proteins structural dynamics is imperative for many biological processes; thus, it is essential to consider the structural dynamics of proteins whilst understanding their function. In this regard, the normal mode analysis (NMA) approach based on the elastic network model (ENM) was employed to study the intrinsic dynamics and conformations changes of GCH1 and PTPS enzymes. The NMA disclosed essential structural information about the protein’s intrinsic dynamics and mechanism of allosteric modulation of their binding properties, further highlighting regions that govern their conformational changes. The analysis also disclosed hotspot residues that are crucial for the proteins' fold stability and function. The NMA was further combined with sequence motif results and showed that conserved residues of GCH1 and PTPS were located within the identified key structural sites modulating the proteins' conformational rearrangement. The characterized structural features and hotspot residues were regarded as potential allosteric sites of important value for the design and development of allosteric drugs. Both GCH1 and PTPS enzymes have never been targeted before and can provide an excellent opportunity to overcome the antimalarial antifolate drug resistance problem. The data presented in this thesis contribute to the understanding of the sequence, structure, and global dynamics of both GCH1 and PTPS, further disclose potential allosteric drug targeting sites and unique structural features of both enzymes that can establish a solid starting point for drug design and development of new antimalarial drugs of a novel mechanism of actions. Lastly, the reported force field parameters will be of value for MD simulations for future in-silico drug discovery studies involving the two enzymes and other enzymes with the same Zn2+ binding motifs and coordination environments. The impact of this research can facilitate the discovery of new effective antimalarial medicines with novel mechanisms of action. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
- Authors: Khairallah, Afrah Yousif Huseein
- Date: 2022-04-08
- Subjects: Antimalarials , Plasmodium falciparum , Malaria Chemotherapy , Malaria Africa , Drug resistance , Drug development , Molecular dynamics
- Language: English
- Type: Doctoral thesis , text
- Identifier: http://hdl.handle.net/10962/233784 , vital:50127 , DOI 10.21504/10962/233784
- Description: Malaria remains a public health problem and a high burden of disease, especially in developing countries. The unicellular protozoan malaria parasite of the genus Plasmodium infects about a quarter of a billion people annually, with an estimated 409 000 death cases. The majority of malaria cases occurred in Africa; hence, the region is regarded as endemic for malaria. Global efforts to eradicate the disease led to a decrease in morbidity and mortality rates. However, an enormous burden of malaria infection remains, and it cannot go unnoticed. Countries with limited resources are more affected by the disease, mainly on its public health and socio-economic development, due to many factors besides malaria itself, such as lack of access to adequate, affordable treatments and preventative regimes. Furthermore, the current antimalarial drugs are losing their efficacy because of parasite drug resistance. The emerged drug resistance has reduced the drug efficacy in clearing the parasite from the host system, causing prolonged illness and a higher risk of death. Therefore, the emerged antimalarial drug resistance has hindered the global efforts for malaria control and elimination and established an urgent need for new treatment strategies. When the resistance against classical antimalarial drugs emerged, the class of antifolate antimalarial medicines became the most common alternative. The antifolate antimalarial drugs target the malaria parasite de novo folate biosynthesis pathway by limiting folate derivates, which are essential for the parasite cell growth and survival. Yet again, the malaria parasite developed resistance against the available antifolate drugs, rendering the drugs ineffective in many cases. Given the previous success in targeting the malaria parasite de novo folate biosynthesis pathway, alternative enzymes within this pathway stand as good targets and can be explored to develop new antifolate drugs with novel mechanisms of action. The primary focus of this thesis is to contribute to the existing and growing knowledge of antimalarial drug discovery. The study aims to characterise the malaria parasite de novo folate synthesis pathway enzymes guanosine-5'-triphosphate (GTP) cyclohydrolase I (GCH1) and 6-pyruvoyl tetrahydropterin synthase (PTPS) as alternative drug targets for malaria treatment by using computational approaches. Further, discover new allosteric drug targeting sites within the two enzymes' 3D structures for future drug design and discovery. Sequence and structural analysis were carried out to characterise and pinpoint the two enzymes' unique sequence and structure-based features. From the analyses, key sequence and structure differences were identified between the malaria parasite enzymes relative to their human homolog; the identified sites can aid significantly in designing and developing new antimalarial antifolate drugs with good selectivity toward the parasites’ enzymes. GCH1 and PTPS contain a catalytically essential metal ion in their active site; therefore, force field parameters were needed to study their active sites accurately during all-atom molecular dynamic simulations (MD). The force field parameters were derived through quantum mechanics potential energy surface scans of the metals bonded terms and evaluated via all-atom MD simulations. Proteins structural dynamics is imperative for many biological processes; thus, it is essential to consider the structural dynamics of proteins whilst understanding their function. In this regard, the normal mode analysis (NMA) approach based on the elastic network model (ENM) was employed to study the intrinsic dynamics and conformations changes of GCH1 and PTPS enzymes. The NMA disclosed essential structural information about the protein’s intrinsic dynamics and mechanism of allosteric modulation of their binding properties, further highlighting regions that govern their conformational changes. The analysis also disclosed hotspot residues that are crucial for the proteins' fold stability and function. The NMA was further combined with sequence motif results and showed that conserved residues of GCH1 and PTPS were located within the identified key structural sites modulating the proteins' conformational rearrangement. The characterized structural features and hotspot residues were regarded as potential allosteric sites of important value for the design and development of allosteric drugs. Both GCH1 and PTPS enzymes have never been targeted before and can provide an excellent opportunity to overcome the antimalarial antifolate drug resistance problem. The data presented in this thesis contribute to the understanding of the sequence, structure, and global dynamics of both GCH1 and PTPS, further disclose potential allosteric drug targeting sites and unique structural features of both enzymes that can establish a solid starting point for drug design and development of new antimalarial drugs of a novel mechanism of actions. Lastly, the reported force field parameters will be of value for MD simulations for future in-silico drug discovery studies involving the two enzymes and other enzymes with the same Zn2+ binding motifs and coordination environments. The impact of this research can facilitate the discovery of new effective antimalarial medicines with novel mechanisms of action. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
Application of computer-aided drug design for identification of P. falciparum inhibitors
- Authors: Diallo, Bakary N’tji
- Date: 2021-10-29
- Subjects: Plasmodium falciparum , Malaria -- Chemotherapy , Molecular dynamics , Antimalarials , Cheminformatics , Drug development , Ligand binding (Biochemistry) , Plasmodium falciparum1-deoxy-D-xylulose-5-phosphate reductoisomerase (PfDXR) , South African Natural Compounds Database
- Language: English
- Type: Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/192798 , vital:45265 , 10.21504/10962/192798
- Description: Malaria is a millennia-old disease with the first recorded cases dating back to 2700 BC found in Chinese medical records, and later in other civilizations. It has claimed human lives to such an extent that there are a notable associated socio-economic consequences. Currently, according to the World Health Organization (WHO), Africa holds the highest disease burden with 94% of deaths and 82% of cases with P. falciparum having ~100% prevalence. Chemotherapy, such as artemisinin combination therapy, has been and continues to be the work horse in the fight against the disease, together with seasonal malaria chemoprevention and the use of insecticides. Natural products such as quinine and artemisinin are particularly important in terms of their antimalarial activity. The emphasis in current chemotherapy research is the need for time and cost-effective workflows focussed on new mechanisms of action (MoAs) covering the target candidate profiles (TCPs). Despite a decline in cases over the past decades with, countries increasingly becoming certified malaria free, a stalling trend has been observed in the past five years resulting in missing the 2020 Global Technical Strategy (GTS) milestones. With no effective vaccine, a reduction in funding, slower drug approval than resistance emergence from resistant and invasive vectors, and threats in diagnosis with the pfhrp2/3 gene deletion, malaria remains a major health concern. Motivated by these reasons, the primary aim of this work was a contribution to the antimalarial pipeline through in silico approaches focusing on P. falciparum. We first intended an exploration of malarial targets through a proteome scale screening on 36 targets using multiple metrics to account for the multi-objective nature of drug discovery. The continuous growth of structural data offers the ideal scenario for mining new MoAs covering antimalarials TCPs. This was combined with a repurposing strategy using a set of orally available FDA approved drugs. Further, use was made of time- and cost-effective strategies combining QVina-W efficiency metrics that integrate molecular properties, GRIM rescoring for molecular interactions and a hydrogen mass repartitioning (HMR) molecular dynamics (MD) scheme for accelerated development of antimalarials in the context of resistance. This pipeline further integrates a complex ranking for better drug-target selectivity, and normalization strategies to overcome docking scoring function bias. The different metrics, ranking, normalization strategies and their combinations were first assessed using their mean ranking error (MRE). A version combining all metrics was used to select 36 unique protein-ligand complexes, assessed in MD, with the final retention of 25. From the 16 in vitro tested hits of the 25, fingolimod, abiraterone, prazosin, and terazosin showed antiplasmodial activity with IC50 2.21, 3.37, 16.67 and 34.72 μM respectively and of these, only fingolimod was found to be not safe with respect to human cell viability. These compounds were predicted active on different molecular targets, abiraterone was predicted to interact with a putative liver-stage essential target, hence promising as a transmission-blocking agent. The pipeline had a promising 25% hit rate considering the proteome-scale and use of cost-effective approaches. Secondly, we focused on Plasmodium falciparum 1-deoxy-D-xylulose-5-phosphate reductoisomerase (PfDXR) using a more extensive screening pipeline to overcome some of the current in silico screening limitations. Starting from the ZINC lead-like library of ~3M, hierarchical ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS) approaches with molecular docking and re-scoring using eleven scoring functions (SFs) were used. Later ranking with an exponential consensus strategy was included. Selected hits were further assessed through Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA), advanced MD sampling in a ligand pulling simulations and (Weighted Histogram Analysis Method) WHAM analysis for umbrella sampling (US) to derive binding free energies. Four leads had better predicted affinities in US than LC5, a 280 nM potent PfDXR inhibitor with ZINC000050633276 showing a promising binding of -20.43 kcal/mol. As shown with fosmidomycin, DXR inhibition offers fast acting compounds fulfilling antimalarials TCP1. Yet, fosmidomycin has a high polarity causing its short half-life and hampering its clinical use. These leads scaffolds are different from fosmidomycin and hence may offer better pharmacokinetic and pharmacodynamic properties and may also be promising for lead optimization. A combined analysis of residues’ contributions to the free energy of binding in MM-PBSA and to steered molecular dynamics (SMD) Fmax indicated GLU233, CYS268, SER270, TRP296, and HIS341 as exploitable for compound optimization. Finally, we updated the SANCDB library with new NPs and their commercially available analogs as a solution to NP availability. The library is extended to 1005 compounds from its initial 600 compounds and the database is integrated to Mcule and Molport APIs for analogs automatic update. The new set may contribute to virtual screening and to antimalarials as the most effective ones have NP origin. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2021
- Full Text:
- Authors: Diallo, Bakary N’tji
- Date: 2021-10-29
- Subjects: Plasmodium falciparum , Malaria -- Chemotherapy , Molecular dynamics , Antimalarials , Cheminformatics , Drug development , Ligand binding (Biochemistry) , Plasmodium falciparum1-deoxy-D-xylulose-5-phosphate reductoisomerase (PfDXR) , South African Natural Compounds Database
- Language: English
- Type: Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/192798 , vital:45265 , 10.21504/10962/192798
- Description: Malaria is a millennia-old disease with the first recorded cases dating back to 2700 BC found in Chinese medical records, and later in other civilizations. It has claimed human lives to such an extent that there are a notable associated socio-economic consequences. Currently, according to the World Health Organization (WHO), Africa holds the highest disease burden with 94% of deaths and 82% of cases with P. falciparum having ~100% prevalence. Chemotherapy, such as artemisinin combination therapy, has been and continues to be the work horse in the fight against the disease, together with seasonal malaria chemoprevention and the use of insecticides. Natural products such as quinine and artemisinin are particularly important in terms of their antimalarial activity. The emphasis in current chemotherapy research is the need for time and cost-effective workflows focussed on new mechanisms of action (MoAs) covering the target candidate profiles (TCPs). Despite a decline in cases over the past decades with, countries increasingly becoming certified malaria free, a stalling trend has been observed in the past five years resulting in missing the 2020 Global Technical Strategy (GTS) milestones. With no effective vaccine, a reduction in funding, slower drug approval than resistance emergence from resistant and invasive vectors, and threats in diagnosis with the pfhrp2/3 gene deletion, malaria remains a major health concern. Motivated by these reasons, the primary aim of this work was a contribution to the antimalarial pipeline through in silico approaches focusing on P. falciparum. We first intended an exploration of malarial targets through a proteome scale screening on 36 targets using multiple metrics to account for the multi-objective nature of drug discovery. The continuous growth of structural data offers the ideal scenario for mining new MoAs covering antimalarials TCPs. This was combined with a repurposing strategy using a set of orally available FDA approved drugs. Further, use was made of time- and cost-effective strategies combining QVina-W efficiency metrics that integrate molecular properties, GRIM rescoring for molecular interactions and a hydrogen mass repartitioning (HMR) molecular dynamics (MD) scheme for accelerated development of antimalarials in the context of resistance. This pipeline further integrates a complex ranking for better drug-target selectivity, and normalization strategies to overcome docking scoring function bias. The different metrics, ranking, normalization strategies and their combinations were first assessed using their mean ranking error (MRE). A version combining all metrics was used to select 36 unique protein-ligand complexes, assessed in MD, with the final retention of 25. From the 16 in vitro tested hits of the 25, fingolimod, abiraterone, prazosin, and terazosin showed antiplasmodial activity with IC50 2.21, 3.37, 16.67 and 34.72 μM respectively and of these, only fingolimod was found to be not safe with respect to human cell viability. These compounds were predicted active on different molecular targets, abiraterone was predicted to interact with a putative liver-stage essential target, hence promising as a transmission-blocking agent. The pipeline had a promising 25% hit rate considering the proteome-scale and use of cost-effective approaches. Secondly, we focused on Plasmodium falciparum 1-deoxy-D-xylulose-5-phosphate reductoisomerase (PfDXR) using a more extensive screening pipeline to overcome some of the current in silico screening limitations. Starting from the ZINC lead-like library of ~3M, hierarchical ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS) approaches with molecular docking and re-scoring using eleven scoring functions (SFs) were used. Later ranking with an exponential consensus strategy was included. Selected hits were further assessed through Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA), advanced MD sampling in a ligand pulling simulations and (Weighted Histogram Analysis Method) WHAM analysis for umbrella sampling (US) to derive binding free energies. Four leads had better predicted affinities in US than LC5, a 280 nM potent PfDXR inhibitor with ZINC000050633276 showing a promising binding of -20.43 kcal/mol. As shown with fosmidomycin, DXR inhibition offers fast acting compounds fulfilling antimalarials TCP1. Yet, fosmidomycin has a high polarity causing its short half-life and hampering its clinical use. These leads scaffolds are different from fosmidomycin and hence may offer better pharmacokinetic and pharmacodynamic properties and may also be promising for lead optimization. A combined analysis of residues’ contributions to the free energy of binding in MM-PBSA and to steered molecular dynamics (SMD) Fmax indicated GLU233, CYS268, SER270, TRP296, and HIS341 as exploitable for compound optimization. Finally, we updated the SANCDB library with new NPs and their commercially available analogs as a solution to NP availability. The library is extended to 1005 compounds from its initial 600 compounds and the database is integrated to Mcule and Molport APIs for analogs automatic update. The new set may contribute to virtual screening and to antimalarials as the most effective ones have NP origin. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2021
- Full Text:
Application of machine learning, molecular modelling and structural data mining against antiretroviral drug resistance in HIV-1
- Sheik Amamuddy, Olivier Serge André
- Authors: Sheik Amamuddy, Olivier Serge André
- Date: 2020
- Subjects: Machine learning , Molecules -- Models , Data mining , Neural networks (Computer science) , Antiretroviral agents , Protease inhibitors , Drug resistance , Multidrug resistance , Molecular dynamics , Renin-angiotensin system , HIV (Viruses) -- South Africa , HIV (Viruses) -- Social aspects -- South Africa , South African Natural Compounds Database
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/115964 , vital:34282
- Description: Millions are affected with the Human Immunodeficiency Virus (HIV) world wide, even though the death toll is on the decline. Antiretrovirals (ARVs), more specifically protease inhibitors have shown tremendous success since their introduction into therapy since the mid 1990’s by slowing down progression to the Acquired Immune Deficiency Syndrome (AIDS). However, Drug Resistance Mutations (DRMs) are constantly selected for due to viral adaptation, making drugs less effective over time. The current challenge is to manage the infection optimally with a limited set of drugs, with differing associated levels of toxicities in the face of a virus that (1) exists as a quasispecies, (2) may transmit acquired DRMs to drug-naive individuals and (3) that can manifest class-wide resistance due to similarities in design. The presence of latent reservoirs, unawareness of infection status, education and various socio-economic factors make the problem even more complex. Adequate timing and choice of drug prescription together with treatment adherence are very important as drug toxicities, drug failure and sub-optimal treatment regimens leave room for further development of drug resistance. While CD4 cell count and the determination of viral load from patients in resource-limited settings are very helpful to track how well a patient’s immune system is able to keep the virus in check, they can be lengthy in determining whether an ARV is effective. Phenosense assay kits answer this problem using viruses engineered to contain the patient sequences and evaluating their growth in the presence of different ARVs, but this can be expensive and too involved for routine checks. As a cheaper and faster alternative, genotypic assays provide similar information from HIV pol sequences obtained from blood samples, inferring ARV efficacy on the basis of drug resistance mutation patterns. However, these are inherently complex and the various methods of in silico prediction, such as Geno2pheno, REGA and Stanford HIVdb do not always agree in every case, even though this gap decreases as the list of resistance mutations is updated. A major gap in HIV treatment is that the information used for predicting drug resistance is mainly computed from data containing an overwhelming majority of B subtype HIV, when these only comprise about 12% of the worldwide HIV infections. In addition to growing evidence that drug resistance is subtype-related, it is intuitive to hypothesize that as subtyping is a phylogenetic classification, the more divergent a subtype is from the strains used in training prediction models, the less their resistance profiles would correlate. For the aforementioned reasons, we used a multi-faceted approach to attack the virus in multiple ways. This research aimed to (1) improve resistance prediction methods by focusing solely on the available subtype, (2) mine structural information pertaining to resistance in order to find any exploitable weak points and increase knowledge of the mechanistic processes of drug resistance in HIV protease. Finally, (3) we screen for protease inhibitors amongst a database of natural compounds [the South African natural compound database (SANCDB)] to find molecules or molecular properties usable to come up with improved inhibition against the drug target. In this work, structural information was mined using the Anisotropic Network Model, Dynamics Cross-Correlation, Perturbation Response Scanning, residue contact network analysis and the radius of gyration. These methods failed to give any resistance-associated patterns in terms of natural movement, internal correlated motions, residue perturbation response, relational behaviour and global compaction respectively. Applications of drug docking, homology-modelling and energy minimization for generating features suitable for machine-learning were not very promising, and rather suggest that the value of binding energies by themselves from Vina may not be very reliable quantitatively. All these failures lead to a refinement that resulted in a highly sensitive statistically-guided network construction and analysis, which leads to key findings in the early dynamics associated with resistance across all PI drugs. The latter experiment unravelled a conserved lateral expansion motion occurring at the flap elbows, and an associated contraction that drives the base of the dimerization domain towards the catalytic site’s floor in the case of drug resistance. Interestingly, we found that despite the conserved movement, bond angles were degenerate. Alongside, 16 Artificial Neural Network models were optimised for HIV proteases and reverse transcriptase inhibitors, with performances on par with Stanford HIVdb. Finally, we prioritised 9 compounds with potential protease inhibitory activity using virtual screening and molecular dynamics (MD) to additionally suggest a promising modification to one of the compounds. This yielded another molecule inhibiting equally well both opened and closed receptor target conformations, whereby each of the compounds had been selected against an array of multi-drug-resistant receptor variants. While a main hurdle was a lack of non-B subtype data, our findings, especially from the statistically-guided network analysis, may extrapolate to a certain extent to them as the level of conservation was very high within subtype B, despite all the present variations. This network construction method lays down a sensitive approach for analysing a pair of alternate phenotypes for which complex patterns prevail, given a sufficient number of experimental units. During the course of research a weighted contact mapping tool was developed to compare renin-angiotensinogen variants and packaged as part of the MD-TASK tool suite. Finally the functionality, compatibility and performance of the MODE-TASK tool were evaluated and confirmed for both Python2.7.x and Python3.x, for the analysis of normals modes from single protein structures and essential modes from MD trajectories. These techniques and tools collectively add onto the conventional means of MD analysis.
- Full Text:
- Authors: Sheik Amamuddy, Olivier Serge André
- Date: 2020
- Subjects: Machine learning , Molecules -- Models , Data mining , Neural networks (Computer science) , Antiretroviral agents , Protease inhibitors , Drug resistance , Multidrug resistance , Molecular dynamics , Renin-angiotensin system , HIV (Viruses) -- South Africa , HIV (Viruses) -- Social aspects -- South Africa , South African Natural Compounds Database
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/115964 , vital:34282
- Description: Millions are affected with the Human Immunodeficiency Virus (HIV) world wide, even though the death toll is on the decline. Antiretrovirals (ARVs), more specifically protease inhibitors have shown tremendous success since their introduction into therapy since the mid 1990’s by slowing down progression to the Acquired Immune Deficiency Syndrome (AIDS). However, Drug Resistance Mutations (DRMs) are constantly selected for due to viral adaptation, making drugs less effective over time. The current challenge is to manage the infection optimally with a limited set of drugs, with differing associated levels of toxicities in the face of a virus that (1) exists as a quasispecies, (2) may transmit acquired DRMs to drug-naive individuals and (3) that can manifest class-wide resistance due to similarities in design. The presence of latent reservoirs, unawareness of infection status, education and various socio-economic factors make the problem even more complex. Adequate timing and choice of drug prescription together with treatment adherence are very important as drug toxicities, drug failure and sub-optimal treatment regimens leave room for further development of drug resistance. While CD4 cell count and the determination of viral load from patients in resource-limited settings are very helpful to track how well a patient’s immune system is able to keep the virus in check, they can be lengthy in determining whether an ARV is effective. Phenosense assay kits answer this problem using viruses engineered to contain the patient sequences and evaluating their growth in the presence of different ARVs, but this can be expensive and too involved for routine checks. As a cheaper and faster alternative, genotypic assays provide similar information from HIV pol sequences obtained from blood samples, inferring ARV efficacy on the basis of drug resistance mutation patterns. However, these are inherently complex and the various methods of in silico prediction, such as Geno2pheno, REGA and Stanford HIVdb do not always agree in every case, even though this gap decreases as the list of resistance mutations is updated. A major gap in HIV treatment is that the information used for predicting drug resistance is mainly computed from data containing an overwhelming majority of B subtype HIV, when these only comprise about 12% of the worldwide HIV infections. In addition to growing evidence that drug resistance is subtype-related, it is intuitive to hypothesize that as subtyping is a phylogenetic classification, the more divergent a subtype is from the strains used in training prediction models, the less their resistance profiles would correlate. For the aforementioned reasons, we used a multi-faceted approach to attack the virus in multiple ways. This research aimed to (1) improve resistance prediction methods by focusing solely on the available subtype, (2) mine structural information pertaining to resistance in order to find any exploitable weak points and increase knowledge of the mechanistic processes of drug resistance in HIV protease. Finally, (3) we screen for protease inhibitors amongst a database of natural compounds [the South African natural compound database (SANCDB)] to find molecules or molecular properties usable to come up with improved inhibition against the drug target. In this work, structural information was mined using the Anisotropic Network Model, Dynamics Cross-Correlation, Perturbation Response Scanning, residue contact network analysis and the radius of gyration. These methods failed to give any resistance-associated patterns in terms of natural movement, internal correlated motions, residue perturbation response, relational behaviour and global compaction respectively. Applications of drug docking, homology-modelling and energy minimization for generating features suitable for machine-learning were not very promising, and rather suggest that the value of binding energies by themselves from Vina may not be very reliable quantitatively. All these failures lead to a refinement that resulted in a highly sensitive statistically-guided network construction and analysis, which leads to key findings in the early dynamics associated with resistance across all PI drugs. The latter experiment unravelled a conserved lateral expansion motion occurring at the flap elbows, and an associated contraction that drives the base of the dimerization domain towards the catalytic site’s floor in the case of drug resistance. Interestingly, we found that despite the conserved movement, bond angles were degenerate. Alongside, 16 Artificial Neural Network models were optimised for HIV proteases and reverse transcriptase inhibitors, with performances on par with Stanford HIVdb. Finally, we prioritised 9 compounds with potential protease inhibitory activity using virtual screening and molecular dynamics (MD) to additionally suggest a promising modification to one of the compounds. This yielded another molecule inhibiting equally well both opened and closed receptor target conformations, whereby each of the compounds had been selected against an array of multi-drug-resistant receptor variants. While a main hurdle was a lack of non-B subtype data, our findings, especially from the statistically-guided network analysis, may extrapolate to a certain extent to them as the level of conservation was very high within subtype B, despite all the present variations. This network construction method lays down a sensitive approach for analysing a pair of alternate phenotypes for which complex patterns prevail, given a sufficient number of experimental units. During the course of research a weighted contact mapping tool was developed to compare renin-angiotensinogen variants and packaged as part of the MD-TASK tool suite. Finally the functionality, compatibility and performance of the MODE-TASK tool were evaluated and confirmed for both Python2.7.x and Python3.x, for the analysis of normals modes from single protein structures and essential modes from MD trajectories. These techniques and tools collectively add onto the conventional means of MD analysis.
- Full Text:
Computer aided approaches against Human African Trypanosomiasis
- Authors: Kimuda, Magambo Phillip
- Date: 2020
- Subjects: African trypanosomiasis , African trypanosomiasis -- Chemotherapy , Genomics , Macrophage migration inhibitory factor , Trypanosoma brucei , Pteridines , Tetrahydrofolate dehydrogenase , Adenylic acid , Molecular dynamics , Principal components analysis , Bioinformatics , Single nucleotide polymorphisms , Single Nucleotide Variants , Candidate Gene Association Study (CGAS)
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/142542 , vital:38089
- Description: The thesis presented here is divided into two parts under a common theme that is the use of computer based tools, genomics, and in vitro experiments to develop innovative ways of tackling Human African Trypanosomiasis (HAT). Part I of this thesis focused on the human host genetic determinants while Part II focused on the discovery of novel chemotherapeutics against the parasite. Part I is further sub-divided into two parts: The first involves a Candidate Gene Association Study (CGAS) on an African population to identify genetic determinants associated with disease and/or susceptibility to HAT. The second involves studying the effects of missense Single Nucleotide Variants (SNVs) on protein structure, dynamics, and function using Macrophage Migration Inhibitory Factor (MIF) as a case study. Part II is also sub-divided into two parts: The first involves a computer based rational drug discovery of potential inhibitors against the Trypanosoma the folate pathway; particularly by targeting Trypanosoma brucei Pteridine Reductase (TbPTR1) which is an enzyme used by trypanosomes to overcome T. brucei Dihydrofolate Reductase (TbDHFR) inhibition. Lastly the derivation of CHARMM force-field parameters that can be used to accurately model the geometry and dynamics of the T. brucei Phosphodiesterase B1 enzyme (TbrPDEB1) bimetallic active site center. The derived parameters were then used in MD simulations to characterise protein-ligand residue interactions that are important in TbrPDEB1 inhibition with the goal of targeting the cyclic Adenosine Monophosphate (cAMP) signalling pathway. In the CGAS we were unable to detect any genetic associations in the Ugandan cohort analysed that passed correction for multiple testing in spite of the study being sufficiently powered. Additionally, our study found no association of the Apo lipoprotein 1 (APOL1) G2 allele association with protection against acute HAT that has been previously reported. Future investigations for example, Genome Wide Association Studies using larger samples sizes (>3000 cases and controls) are required. Macrophage migration inhibitory factor (MIF) is a cytokine that is important in both innate and adaptive immunity that has been shown to play a role in T. brucei pathogenicity using murine models. A total of 27 missense SNVs were modelled using homology modelling to create MIF protein mutants that were investigated using in silico effect prediction tools, molecular dynamics (MD), Principal Component Analysis (PCA), and Dynamic Residue Network (DRN) analysis. Our results demonstrate that mutations P2Q, I5M, P16Q, L23F, T24S, T31I, Y37H, H41P, M48V, P44L, G52C, S54R, I65M, I68T, S75F, N106S, and T113S caused significant conformational changes. Further, DRN analysis showed that residues P2, T31, Y37, G52, I65, I68, S75, N106, and T113S are part of a similar local residue interaction network with functional significance. These results show how polymorphisms such as missense SNVs can affect protein conformation, dynamics, and function. Trypanosomes are auxotrophic for folates and pterins but require them for survival. They scavenge them from their hosts. PTR1 is a multifunctional enzyme that is unique to trypanosomatids that reduces both pterins and folates. In the presence of DHFR inhibitors, PTR1 is over-expressed thus providing an escape from the effects of DHFR inhibition. Both TbPTR1 and TbDHFR are pharmacologically and genetically validated drug targets. In this study 5742 compounds were screened using molecular docking, and 13 promising binding modes were further analysed using MD simulations. The trajectories were analysed using RMSD, Rg, RMSF, PCA, Essential Dynamics Analysis (EDA), Molecular Mechanics Poisson–Boltzmann surface area (MM-PBSA) binding free energy calculations, and DRN analysis. The computational screening approach allowed us to identify five of the compounds, named RUBi004, RUBi007, RUBi014, RUBi016 and RUBi018 that exhibited antitrypanosomal growth activities against trypanosomes in culture with IC50 values of 12.5 ± 4.8 μM, 32.4 ± 4.2 μM, 5.9 ± 1.4 μM, 28.2 ± 3.3 μM, and 9.7 ± 2.1 μM, respectively. Further when used in combination with WR99210 a known TbDHFR inhibitor RUBi004, RUBi007, RUBi014 and RUBi018 showed antagonism while RUBi016 showed an additive effect. These results indicate that the four compounds might be competing with TbDHFR while RUBi016 might be more specific for TbPTR1. These compounds provide scaffolds that can be further optimised to improve their potency and specificity. Lastly, using a systematic approach we derived CHARMM force-field parameters to accurately describe the TbrPDEB1 bi-metal catalytic center. For dynamics, we employed mixed bonded and non-bonded approach. We optimised the structure using a two-layer QM/MM ONIOM (B3LYP/6-31(g): UFF). The TbrPDEB1 bi-metallic center bonds, angles, and dihedrals were parameterized by fitting the energy profiles from Potential Energy Surface (PES) scans to the CHARMM potential energy function. The parameters were validated by means of MD simulations and analysed using RMSD, Rg, RMSF, hydrogen bonding, bond/angle/dihedral evaluations, EDA, PCA, and DRN analysis. The force-field parameters were able to accurately reproduce the geometry and dynamics of the TbrPDEB1 bi-metal catalytic center during MD simulations. Molecular docking was used to identify 6 potential hits, that inhibited trypanosome growth in vitro. The derived force-field parameters were used to simulate the 6 protein-ligand complexes with the aim of elucidating crucial protein-ligand residue interactions. Using the most potent ligand RUBi022 that had an IC50 of 14.96 μM we were able to identify key residue interactions that can be of use in in silico prediction of potential TbrPDEB1 inhibitors. Overall we demonstrate how bioinformatics tools can complement current disease eradication strategies. Future work will focus on identifying variants identified in Genome Wide Association Studies and partnering with wet labs to carry out further enzyme-ligand activity relationship studies, structure determination or characterisation of appropriate protein-ligand complexes by crystallography, and site specific mutation studies
- Full Text:
- Authors: Kimuda, Magambo Phillip
- Date: 2020
- Subjects: African trypanosomiasis , African trypanosomiasis -- Chemotherapy , Genomics , Macrophage migration inhibitory factor , Trypanosoma brucei , Pteridines , Tetrahydrofolate dehydrogenase , Adenylic acid , Molecular dynamics , Principal components analysis , Bioinformatics , Single nucleotide polymorphisms , Single Nucleotide Variants , Candidate Gene Association Study (CGAS)
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/142542 , vital:38089
- Description: The thesis presented here is divided into two parts under a common theme that is the use of computer based tools, genomics, and in vitro experiments to develop innovative ways of tackling Human African Trypanosomiasis (HAT). Part I of this thesis focused on the human host genetic determinants while Part II focused on the discovery of novel chemotherapeutics against the parasite. Part I is further sub-divided into two parts: The first involves a Candidate Gene Association Study (CGAS) on an African population to identify genetic determinants associated with disease and/or susceptibility to HAT. The second involves studying the effects of missense Single Nucleotide Variants (SNVs) on protein structure, dynamics, and function using Macrophage Migration Inhibitory Factor (MIF) as a case study. Part II is also sub-divided into two parts: The first involves a computer based rational drug discovery of potential inhibitors against the Trypanosoma the folate pathway; particularly by targeting Trypanosoma brucei Pteridine Reductase (TbPTR1) which is an enzyme used by trypanosomes to overcome T. brucei Dihydrofolate Reductase (TbDHFR) inhibition. Lastly the derivation of CHARMM force-field parameters that can be used to accurately model the geometry and dynamics of the T. brucei Phosphodiesterase B1 enzyme (TbrPDEB1) bimetallic active site center. The derived parameters were then used in MD simulations to characterise protein-ligand residue interactions that are important in TbrPDEB1 inhibition with the goal of targeting the cyclic Adenosine Monophosphate (cAMP) signalling pathway. In the CGAS we were unable to detect any genetic associations in the Ugandan cohort analysed that passed correction for multiple testing in spite of the study being sufficiently powered. Additionally, our study found no association of the Apo lipoprotein 1 (APOL1) G2 allele association with protection against acute HAT that has been previously reported. Future investigations for example, Genome Wide Association Studies using larger samples sizes (>3000 cases and controls) are required. Macrophage migration inhibitory factor (MIF) is a cytokine that is important in both innate and adaptive immunity that has been shown to play a role in T. brucei pathogenicity using murine models. A total of 27 missense SNVs were modelled using homology modelling to create MIF protein mutants that were investigated using in silico effect prediction tools, molecular dynamics (MD), Principal Component Analysis (PCA), and Dynamic Residue Network (DRN) analysis. Our results demonstrate that mutations P2Q, I5M, P16Q, L23F, T24S, T31I, Y37H, H41P, M48V, P44L, G52C, S54R, I65M, I68T, S75F, N106S, and T113S caused significant conformational changes. Further, DRN analysis showed that residues P2, T31, Y37, G52, I65, I68, S75, N106, and T113S are part of a similar local residue interaction network with functional significance. These results show how polymorphisms such as missense SNVs can affect protein conformation, dynamics, and function. Trypanosomes are auxotrophic for folates and pterins but require them for survival. They scavenge them from their hosts. PTR1 is a multifunctional enzyme that is unique to trypanosomatids that reduces both pterins and folates. In the presence of DHFR inhibitors, PTR1 is over-expressed thus providing an escape from the effects of DHFR inhibition. Both TbPTR1 and TbDHFR are pharmacologically and genetically validated drug targets. In this study 5742 compounds were screened using molecular docking, and 13 promising binding modes were further analysed using MD simulations. The trajectories were analysed using RMSD, Rg, RMSF, PCA, Essential Dynamics Analysis (EDA), Molecular Mechanics Poisson–Boltzmann surface area (MM-PBSA) binding free energy calculations, and DRN analysis. The computational screening approach allowed us to identify five of the compounds, named RUBi004, RUBi007, RUBi014, RUBi016 and RUBi018 that exhibited antitrypanosomal growth activities against trypanosomes in culture with IC50 values of 12.5 ± 4.8 μM, 32.4 ± 4.2 μM, 5.9 ± 1.4 μM, 28.2 ± 3.3 μM, and 9.7 ± 2.1 μM, respectively. Further when used in combination with WR99210 a known TbDHFR inhibitor RUBi004, RUBi007, RUBi014 and RUBi018 showed antagonism while RUBi016 showed an additive effect. These results indicate that the four compounds might be competing with TbDHFR while RUBi016 might be more specific for TbPTR1. These compounds provide scaffolds that can be further optimised to improve their potency and specificity. Lastly, using a systematic approach we derived CHARMM force-field parameters to accurately describe the TbrPDEB1 bi-metal catalytic center. For dynamics, we employed mixed bonded and non-bonded approach. We optimised the structure using a two-layer QM/MM ONIOM (B3LYP/6-31(g): UFF). The TbrPDEB1 bi-metallic center bonds, angles, and dihedrals were parameterized by fitting the energy profiles from Potential Energy Surface (PES) scans to the CHARMM potential energy function. The parameters were validated by means of MD simulations and analysed using RMSD, Rg, RMSF, hydrogen bonding, bond/angle/dihedral evaluations, EDA, PCA, and DRN analysis. The force-field parameters were able to accurately reproduce the geometry and dynamics of the TbrPDEB1 bi-metal catalytic center during MD simulations. Molecular docking was used to identify 6 potential hits, that inhibited trypanosome growth in vitro. The derived force-field parameters were used to simulate the 6 protein-ligand complexes with the aim of elucidating crucial protein-ligand residue interactions. Using the most potent ligand RUBi022 that had an IC50 of 14.96 μM we were able to identify key residue interactions that can be of use in in silico prediction of potential TbrPDEB1 inhibitors. Overall we demonstrate how bioinformatics tools can complement current disease eradication strategies. Future work will focus on identifying variants identified in Genome Wide Association Studies and partnering with wet labs to carry out further enzyme-ligand activity relationship studies, structure determination or characterisation of appropriate protein-ligand complexes by crystallography, and site specific mutation studies
- Full Text:
Cyclooxygenase-1 as an anti-stroke target: potential inhibitor identification and non-synonymous single nucleotide polymorphism analysis
- Authors: Muronzi, Tendai
- Date: 2020
- Subjects: Cerebrovascular disease , Cerebrovascular disease -- Treatment , Cerebrovascular disease -- Chemotherapy , Cyclooxygenases , High throughput screening (Drug development) , Drug development , Molecular dynamics , South African Natural Compounds Database , ZINC database
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/143404 , vital:38243
- Description: Stroke is the third leading cause of death worldwide, with 87% of cases being ischemic stroke. The two primary therapeutic strategies to reduce post-ischemic brain damage are cellular and vascular approaches. The vascular strategy aims to rapidly re-open obstructed blood vessels, while the cellular approach aims to interfere with the signalling pathways that facilitate neuron damage and death. Unfortunately, popular vascular treatments have adverse side effects, necessitating the need for alternative chemotherapeutics. In this study, cyclooxygenase-1 (COX-1), which plays a significant role in the post- ischemic neuroinflammation and neuronal death, was targeted for identification of novel drug compounds and to assess the effect of nsSNPs on its structure and function. In a drug discovery part, ligands from the South African Natural Compounds Database (SANCDB-https://sancdb.rubi.ru.ac.za/) and ZINC database (http://zinc15.docking.org/) were used for high-throughput virtual screening (HVTS) against COX-1. Additionally, five nsSNPs were being investigated to assess their impact on protein structure and function. Three of these SNPs were in the COX-1 dimer interface. Molecular docking and molecular dynamics simulations revealed asymmetric nature of the protein. Several ligands, peculiar to each monomer, exhibited favourable binding energies in the respective active sites. SNP analysis indicated effects on inter-monomer interactions and protein stability.
- Full Text:
- Authors: Muronzi, Tendai
- Date: 2020
- Subjects: Cerebrovascular disease , Cerebrovascular disease -- Treatment , Cerebrovascular disease -- Chemotherapy , Cyclooxygenases , High throughput screening (Drug development) , Drug development , Molecular dynamics , South African Natural Compounds Database , ZINC database
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/143404 , vital:38243
- Description: Stroke is the third leading cause of death worldwide, with 87% of cases being ischemic stroke. The two primary therapeutic strategies to reduce post-ischemic brain damage are cellular and vascular approaches. The vascular strategy aims to rapidly re-open obstructed blood vessels, while the cellular approach aims to interfere with the signalling pathways that facilitate neuron damage and death. Unfortunately, popular vascular treatments have adverse side effects, necessitating the need for alternative chemotherapeutics. In this study, cyclooxygenase-1 (COX-1), which plays a significant role in the post- ischemic neuroinflammation and neuronal death, was targeted for identification of novel drug compounds and to assess the effect of nsSNPs on its structure and function. In a drug discovery part, ligands from the South African Natural Compounds Database (SANCDB-https://sancdb.rubi.ru.ac.za/) and ZINC database (http://zinc15.docking.org/) were used for high-throughput virtual screening (HVTS) against COX-1. Additionally, five nsSNPs were being investigated to assess their impact on protein structure and function. Three of these SNPs were in the COX-1 dimer interface. Molecular docking and molecular dynamics simulations revealed asymmetric nature of the protein. Several ligands, peculiar to each monomer, exhibited favourable binding energies in the respective active sites. SNP analysis indicated effects on inter-monomer interactions and protein stability.
- Full Text:
Mechanism of action of non-synonymous single nucleotide variations associated with α-carbonic anhydrases II, IV and VIII
- Authors: Sanyanga, T. Allan
- Date: 2020
- Subjects: Carbonic anhydrase , Carbonic anhydrase -- Therapeutic use , Nucleotides
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/167346 , vital:41470
- Description: The carbonic anhydrase (CA) group of enzymes are Zinc (Zn2+) metalloproteins responsible for the reversible hydration of CO2 to bicarbonate (BCT or HCO− 3 ) and protons (H+) for the facilitation of acid-base balance and homeostasis within the body. Across all organisms, a minimum of six CA families exist, including, α (alpha), β (beta), γ (gamma), δ (delta), η (eta) and ζ (zeta). Some organisms can have more than one family, with exception to humans that contain the α family solely. The α-CA family comprises of 16 isoforms (CA-I to CA-XV) including the CA-VIII, CA-X and CA-XI acatalytic isoforms. Of the catalytic isoforms, CA-II and CA-IV possess one of the fastest rates of reaction, and any disturbances to the function of these enzymes results in CA deficiencies and undesirable phenotypes. CA-II deficiencies result in osteopetrosis with renal tubular acidosis and cerebral calcification, whereas CA-IV deficiencies result in retinitis pigmentosa 17 (RP17). Phenotypic effects generally manifest as a result of poor protein folding and function due to the presence of non-synonymous single nucleotide variations (nsSNVs). Even within the acatalytic isoforms such as CA-VIII that llosterically regulates the affinity of inositol triphosphate (IP3) for the IP3 receptor type 1 (ITPR1) and regulates calcium (Ca2+) signalling, the presence of SNVs also causes phenotypes cerebellar ataxia, mental retardation, and dysequilibrium syndrome 3 (CAMRQ3). Currently the majority of research into the CAs is focused on the inhibition of these proteins to achieve therapeutic effects in patients via the control of HCO− production or reabsorption as observed in glaucoma and diuretic medications. Little research has therefore been devoted into the identification of stabilising or activating compound that could rescue protein function in the case of deficiencies. The main aim of this research was to identify and characterise the effects of nsSNVs on the structure and function of CA-II, CA-IV and CA-VIII to set a foundation for rare disease studies into the CA group of proteins. Combined bioinformatics approaches divided into four main objectives were implemented. These included variant identification, sequence analysis and protein characterisation, force field (FF) parameter generation, molecular dynamics (MD) simulation and dynamic residue network analysis (DRN). Six variants for each of the CA-II, CA-IV and CA-VIII proteins with pathogenic annotations were identified from the HUMA and Ensembl databases. These included the pathogenic variants K18E, K18Q, H107Y, P236H, P236R and N252D for CA-II. CA-IV included the pathogenic R69H, R219C and R219S, and benign N86K, N177K and V234I variants. CA-VIII included pathogenic S100A, S100P, G162R and R237Q, and benign S100L and E109D variants. CA-II has been more extensively studied than CA-IV and CA-VIII, therefore residues essential to its function and stability are known. To discover important residues and regions within the CA-IV and CA-VIII proteins sequence and motif analysis was performed across the α-CA family, using CA-II as a reference. Sequence analysis identified multiple conserved residues between the two acatalytic CA-II and CA-IV, and the acatalytic CA-VIII isoforms that were proposed to be essential for protein stability. With exception to the benign N86K CA-IV variant, none of the other pathogenic or benign CA-II, CA-IV and CA-VIII SNVs were located at functionally or structurally important residues. Motif analysis identified 11 conserved and important motifs within the α-CA family. Several of the identified variants were located on these motifs including K18E, K18Q, H107Y and N252D (CA-II); N86K, R219C, R219S and V234I (CA-IV); and E109D, G162R and R237Q (CA-VIII). As there were no x-ray crystal structures of the variant proteins, homology modelling was performed to calculate the protein structures for characterisation. In CA-VIII, the substitution of Ser for Pro at position 100 (variant S100P) resulted in destruction of the β-sheet that the SNV was located on. Little is known about the mechanism of interaction between CA-VIII and ITPR1, and residues involved. SiteMap and CPORT were used to identify binding site amino for CA-VIII and results identified 38 potential residues. Traditional FFs are incapable of performing MD simulations of metalloproteins. The AMBER ff14SB FF was extended and Zn2+ FF parameters calculated to add support for metalloprotein MD simulations. In the protein, Zn2+ was noted to have a charge less than +1. Variant effects on protein structure were then investigated using MD simulations. Root mean square deviation (RMSD) and radius of gyration (Rg) results indicated subtle SNV effects to the variant global structure in CA-II and CA-IV. However, with regards to CA-VIII RMSD analysis highlighted that variant presence was associated with increases to the structural rigidity of the protein. Principal component analysis (PCA) in conjunction with free energy analysis was performed to observe variant effects on protein conformational sampling in 3D space. The binding of BCT to CA-II induced greater protein conformational sampling and was associated with higher free energy. In CA-IV and CA-VIII PCA analysis revealed key differences in the mechanism of action of pathogenic and benign SNVs. In CA-IV, wild-type (WT) and benign variant protein structures clustered into single low energy well hinting at the presence of more stable structures. Pathogenic variants were associated with higher free energy and proteins sampled more conformations without settling into a low energy well. PCA analysis of CA-VIII indicated the opposite to CA-IV. Pathogenic variants were clustered into low energy wells, while the WT and benign variants showed greater conformational sampling. Dynamic cross correlation (DCC) analysis was performed using the MD-TASK suite to determine variant effects on residue movement. CA-II WT protein revealed that BCT and CO2 were associated with anti-correlated and correlated residue movement, highlighting at opposite mechanisms. In CA-IV and CA-VIII variant presence resulted in a change to residue correlation compared to the WT proteins. DRN analysis was performed to investigate SNV effects of residue accessibility and communication. Results demonstrated that SNVs are associated with allosteric effects on the CA protein structures, and effects are located on the stability assisting residues of the aromatic clusters and the active site of the proteins. CA-II studies discovered that Glu117 is the most important residue for communication, and variant presence results in a decrease to the usage of the residue. This effect was greatest in the CA-II H107Y SNV, and suggests that variants could have an effect on Zn2+ dissociation from the active site. Decreases to the usage of Zn2+ coordinating residues were also noted. Where this occurred, compensatory increases to the usage of other primary and secondary coordination residues were observed, that could possibly assist with the maintenance of Zn2+ within the active site. The CA-IV variants R69H and R219C highlighted potentially similar pathogenic mechanisms, whereas N86K and N177K hinted at potentially similar benign mechanisms. Within CA-VIII, variant presence was associated with changes to the accessibility of the N-terminal binding site residues. The benign CA-VIII variants highlighted possible compensatory mechanisms, whereby as one group of N-terminal residues loses accessibility, there was an increase to the accessibility of other binding site residues to possibly balance the effect. Catalytically, the proton shuttle residue His64 in CA-II was found to occupy a novel conformation named the “faux in” that brought the imidazole group even closer to the Zn2+ compared to the “in” conformation. Overall, compared to traditional MD simulations the incorporation of DRN allowed more detailed investigations into the variant mechanisms of action. This highlights the importance of network analysis in the study of the effects of missense mutations on the structure and function of proteins. Investigations of diseases at the molecular level is essential in the identification of disease pathogenesis and assists with the development of specifically tailored and better treatment options especially in the cases of genetically associated rare diseases.
- Full Text:
- Authors: Sanyanga, T. Allan
- Date: 2020
- Subjects: Carbonic anhydrase , Carbonic anhydrase -- Therapeutic use , Nucleotides
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/167346 , vital:41470
- Description: The carbonic anhydrase (CA) group of enzymes are Zinc (Zn2+) metalloproteins responsible for the reversible hydration of CO2 to bicarbonate (BCT or HCO− 3 ) and protons (H+) for the facilitation of acid-base balance and homeostasis within the body. Across all organisms, a minimum of six CA families exist, including, α (alpha), β (beta), γ (gamma), δ (delta), η (eta) and ζ (zeta). Some organisms can have more than one family, with exception to humans that contain the α family solely. The α-CA family comprises of 16 isoforms (CA-I to CA-XV) including the CA-VIII, CA-X and CA-XI acatalytic isoforms. Of the catalytic isoforms, CA-II and CA-IV possess one of the fastest rates of reaction, and any disturbances to the function of these enzymes results in CA deficiencies and undesirable phenotypes. CA-II deficiencies result in osteopetrosis with renal tubular acidosis and cerebral calcification, whereas CA-IV deficiencies result in retinitis pigmentosa 17 (RP17). Phenotypic effects generally manifest as a result of poor protein folding and function due to the presence of non-synonymous single nucleotide variations (nsSNVs). Even within the acatalytic isoforms such as CA-VIII that llosterically regulates the affinity of inositol triphosphate (IP3) for the IP3 receptor type 1 (ITPR1) and regulates calcium (Ca2+) signalling, the presence of SNVs also causes phenotypes cerebellar ataxia, mental retardation, and dysequilibrium syndrome 3 (CAMRQ3). Currently the majority of research into the CAs is focused on the inhibition of these proteins to achieve therapeutic effects in patients via the control of HCO− production or reabsorption as observed in glaucoma and diuretic medications. Little research has therefore been devoted into the identification of stabilising or activating compound that could rescue protein function in the case of deficiencies. The main aim of this research was to identify and characterise the effects of nsSNVs on the structure and function of CA-II, CA-IV and CA-VIII to set a foundation for rare disease studies into the CA group of proteins. Combined bioinformatics approaches divided into four main objectives were implemented. These included variant identification, sequence analysis and protein characterisation, force field (FF) parameter generation, molecular dynamics (MD) simulation and dynamic residue network analysis (DRN). Six variants for each of the CA-II, CA-IV and CA-VIII proteins with pathogenic annotations were identified from the HUMA and Ensembl databases. These included the pathogenic variants K18E, K18Q, H107Y, P236H, P236R and N252D for CA-II. CA-IV included the pathogenic R69H, R219C and R219S, and benign N86K, N177K and V234I variants. CA-VIII included pathogenic S100A, S100P, G162R and R237Q, and benign S100L and E109D variants. CA-II has been more extensively studied than CA-IV and CA-VIII, therefore residues essential to its function and stability are known. To discover important residues and regions within the CA-IV and CA-VIII proteins sequence and motif analysis was performed across the α-CA family, using CA-II as a reference. Sequence analysis identified multiple conserved residues between the two acatalytic CA-II and CA-IV, and the acatalytic CA-VIII isoforms that were proposed to be essential for protein stability. With exception to the benign N86K CA-IV variant, none of the other pathogenic or benign CA-II, CA-IV and CA-VIII SNVs were located at functionally or structurally important residues. Motif analysis identified 11 conserved and important motifs within the α-CA family. Several of the identified variants were located on these motifs including K18E, K18Q, H107Y and N252D (CA-II); N86K, R219C, R219S and V234I (CA-IV); and E109D, G162R and R237Q (CA-VIII). As there were no x-ray crystal structures of the variant proteins, homology modelling was performed to calculate the protein structures for characterisation. In CA-VIII, the substitution of Ser for Pro at position 100 (variant S100P) resulted in destruction of the β-sheet that the SNV was located on. Little is known about the mechanism of interaction between CA-VIII and ITPR1, and residues involved. SiteMap and CPORT were used to identify binding site amino for CA-VIII and results identified 38 potential residues. Traditional FFs are incapable of performing MD simulations of metalloproteins. The AMBER ff14SB FF was extended and Zn2+ FF parameters calculated to add support for metalloprotein MD simulations. In the protein, Zn2+ was noted to have a charge less than +1. Variant effects on protein structure were then investigated using MD simulations. Root mean square deviation (RMSD) and radius of gyration (Rg) results indicated subtle SNV effects to the variant global structure in CA-II and CA-IV. However, with regards to CA-VIII RMSD analysis highlighted that variant presence was associated with increases to the structural rigidity of the protein. Principal component analysis (PCA) in conjunction with free energy analysis was performed to observe variant effects on protein conformational sampling in 3D space. The binding of BCT to CA-II induced greater protein conformational sampling and was associated with higher free energy. In CA-IV and CA-VIII PCA analysis revealed key differences in the mechanism of action of pathogenic and benign SNVs. In CA-IV, wild-type (WT) and benign variant protein structures clustered into single low energy well hinting at the presence of more stable structures. Pathogenic variants were associated with higher free energy and proteins sampled more conformations without settling into a low energy well. PCA analysis of CA-VIII indicated the opposite to CA-IV. Pathogenic variants were clustered into low energy wells, while the WT and benign variants showed greater conformational sampling. Dynamic cross correlation (DCC) analysis was performed using the MD-TASK suite to determine variant effects on residue movement. CA-II WT protein revealed that BCT and CO2 were associated with anti-correlated and correlated residue movement, highlighting at opposite mechanisms. In CA-IV and CA-VIII variant presence resulted in a change to residue correlation compared to the WT proteins. DRN analysis was performed to investigate SNV effects of residue accessibility and communication. Results demonstrated that SNVs are associated with allosteric effects on the CA protein structures, and effects are located on the stability assisting residues of the aromatic clusters and the active site of the proteins. CA-II studies discovered that Glu117 is the most important residue for communication, and variant presence results in a decrease to the usage of the residue. This effect was greatest in the CA-II H107Y SNV, and suggests that variants could have an effect on Zn2+ dissociation from the active site. Decreases to the usage of Zn2+ coordinating residues were also noted. Where this occurred, compensatory increases to the usage of other primary and secondary coordination residues were observed, that could possibly assist with the maintenance of Zn2+ within the active site. The CA-IV variants R69H and R219C highlighted potentially similar pathogenic mechanisms, whereas N86K and N177K hinted at potentially similar benign mechanisms. Within CA-VIII, variant presence was associated with changes to the accessibility of the N-terminal binding site residues. The benign CA-VIII variants highlighted possible compensatory mechanisms, whereby as one group of N-terminal residues loses accessibility, there was an increase to the accessibility of other binding site residues to possibly balance the effect. Catalytically, the proton shuttle residue His64 in CA-II was found to occupy a novel conformation named the “faux in” that brought the imidazole group even closer to the Zn2+ compared to the “in” conformation. Overall, compared to traditional MD simulations the incorporation of DRN allowed more detailed investigations into the variant mechanisms of action. This highlights the importance of network analysis in the study of the effects of missense mutations on the structure and function of proteins. Investigations of diseases at the molecular level is essential in the identification of disease pathogenesis and assists with the development of specifically tailored and better treatment options especially in the cases of genetically associated rare diseases.
- Full Text:
Understanding of the underlying resistance mechanism of the Kat-G protein against isoniazid in Mycobacterium tuberculosis using bioinformatics approaches
- Authors: Barozi, Victor
- Date: 2020
- Subjects: Mycobacterium tuberculosis , Isoniazid , Drug resistance in microorganisms , Proteins -- Microbiology
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/146592 , vital:38540
- Description: Tuberculosis (TB) is a multi-organ infection caused by rod-shaped acid-fast Mycobacterium tuberculosis. The World Health Organization (WHO) ranks TB among the top 10 fatal infections and the leading the cause of death from a single infection. In 2017, TB was responsible for an estimated 1.3 million deaths among both the HIV negative and positive populations worldwide (WHO, 2018). Approximately 23% (roughly 1.7 billion) of the world’s population is estimated to have latent TB with a high risk of reverting to active TB infection. In 2017, an estimated 558,000 people developed drug resistant TB worldwide with 82% of the cases being multi-drug resistant TB (WHO, 2018). South Africa is ranked among the 30 high TB burdened countries with a TB incidence of 322,000 cases in 2017 accounting for 3% of the world’s TB cases. TB is curable and is clinically managed through a combination of intensive and continuation phases of first-line drugs (isoniazid, rifampicin, ethambutol, and pyrazinamide). Second-line drugs which include fluoroquinolones, injectable aminoglycoside and injectable polypeptides are used in cases of first line drug resistance. The third-line drugs include amoxicillin, clofazimine, linezolid and imipenem. These have variable but unproven efficacy to TB and are the last resort in cases of total drug resistance (Jilani et al., 2019). TB drug resistance to first-line drugs especially isoniazid in M. tuberculosis has been attributed to single nucleotide polymorphisms (SNPs) in the catalase peroxidase enzyme (katG), a protein important in the activation of the pro-drug isoniazid. The SNPs especially at position 315 of the katG enzyme are believed to reduce the sensitivity of the M. tuberculosis to isoniazid while still maintaining the enzyme’s catalytic activity - a mechanism not completely understood. KatG protein is important for protecting the bacteria from hydro peroxides and hydroxyl radicals present in an aerobic environment. This study focused on understanding the mechanism of isoniazid drug resistance in M. tuberculosis as a result of high confidence mutations in the katG through modelling the enzyme with its respective variants, performing MD simulations to explore the protein behaviour, calculating the dynamic residue network analysis (DRN) of the variants in respect to the wild type katG and finally performing alanine scanning. From the MD simulations, it was observed that the high confidence mutations i.e. S140R, S140N, G279D, G285D, S315T, S315I, S315R, S315N, G316D, S457I and G593D were not only reducing the backbone flexibility of the protein but also reducing the protein’s conformational variation and space. All the variant protein structures were observed to be more compact compared to the wild type. Residue fluctuation results indicated reduced residue flexibility across all variants in the loop region (position 26-110) responsible for katG dimerization. In addition, mutation S315T is believed to reduce the size of the active site access channel in the protein. From the DRN data, residues in the interface region between the N and C-terminal domains were observed to gain importance in the variants irrespective of the mutation location indicating an allosteric effect of the mutations on the interface region. Alanine scanning results established that residue Leucine at position 48 was not only important in the protein communication but also a destabilizing residue across all the variants. The study not only demonstrated change in the protein behaviour but also showed allosteric effect of the mutations in the katG protein.
- Full Text:
- Authors: Barozi, Victor
- Date: 2020
- Subjects: Mycobacterium tuberculosis , Isoniazid , Drug resistance in microorganisms , Proteins -- Microbiology
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/146592 , vital:38540
- Description: Tuberculosis (TB) is a multi-organ infection caused by rod-shaped acid-fast Mycobacterium tuberculosis. The World Health Organization (WHO) ranks TB among the top 10 fatal infections and the leading the cause of death from a single infection. In 2017, TB was responsible for an estimated 1.3 million deaths among both the HIV negative and positive populations worldwide (WHO, 2018). Approximately 23% (roughly 1.7 billion) of the world’s population is estimated to have latent TB with a high risk of reverting to active TB infection. In 2017, an estimated 558,000 people developed drug resistant TB worldwide with 82% of the cases being multi-drug resistant TB (WHO, 2018). South Africa is ranked among the 30 high TB burdened countries with a TB incidence of 322,000 cases in 2017 accounting for 3% of the world’s TB cases. TB is curable and is clinically managed through a combination of intensive and continuation phases of first-line drugs (isoniazid, rifampicin, ethambutol, and pyrazinamide). Second-line drugs which include fluoroquinolones, injectable aminoglycoside and injectable polypeptides are used in cases of first line drug resistance. The third-line drugs include amoxicillin, clofazimine, linezolid and imipenem. These have variable but unproven efficacy to TB and are the last resort in cases of total drug resistance (Jilani et al., 2019). TB drug resistance to first-line drugs especially isoniazid in M. tuberculosis has been attributed to single nucleotide polymorphisms (SNPs) in the catalase peroxidase enzyme (katG), a protein important in the activation of the pro-drug isoniazid. The SNPs especially at position 315 of the katG enzyme are believed to reduce the sensitivity of the M. tuberculosis to isoniazid while still maintaining the enzyme’s catalytic activity - a mechanism not completely understood. KatG protein is important for protecting the bacteria from hydro peroxides and hydroxyl radicals present in an aerobic environment. This study focused on understanding the mechanism of isoniazid drug resistance in M. tuberculosis as a result of high confidence mutations in the katG through modelling the enzyme with its respective variants, performing MD simulations to explore the protein behaviour, calculating the dynamic residue network analysis (DRN) of the variants in respect to the wild type katG and finally performing alanine scanning. From the MD simulations, it was observed that the high confidence mutations i.e. S140R, S140N, G279D, G285D, S315T, S315I, S315R, S315N, G316D, S457I and G593D were not only reducing the backbone flexibility of the protein but also reducing the protein’s conformational variation and space. All the variant protein structures were observed to be more compact compared to the wild type. Residue fluctuation results indicated reduced residue flexibility across all variants in the loop region (position 26-110) responsible for katG dimerization. In addition, mutation S315T is believed to reduce the size of the active site access channel in the protein. From the DRN data, residues in the interface region between the N and C-terminal domains were observed to gain importance in the variants irrespective of the mutation location indicating an allosteric effect of the mutations on the interface region. Alanine scanning results established that residue Leucine at position 48 was not only important in the protein communication but also a destabilizing residue across all the variants. The study not only demonstrated change in the protein behaviour but also showed allosteric effect of the mutations in the katG protein.
- Full Text:
Understanding the underlying resistance mechanism of Mycobacterium tuberculosis against Rifampicin by analyzing mutant DNA - directed RNA polymerase proteins via bioinformatics approaches
- Authors: Monama, Mokgerwa Zacharia
- Date: 2020
- Subjects: Mycobacterium tuberculosis , Rifampin , Drug resistance , Homology (Biology) , Tuberculosis -- Chemotherapy
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/167508 , vital:41487
- Description: Tuberculosis or TB is an airborne disease caused by the non-motile bacilli, Mycobacterium tuberculosis (MTB). There are two main forms of TB, namely, latent TB or LTB, asymptomatic and non-contagious version which according to the World Health Organization (WHO) is estimated to afflict over a third of the world’s population; and active TB or ATB, a symptomatic and contagious version which continues to spread, affecting millions worldwide. With the already high reported prevalence of TB, the emergence of drug-resistant strains has prompted the development of novel approaches to enhance the efficacy of known drugs and a desperate search for novel compounds to combat MTB infections. It was for this very purpose that this study was conducted. A look into the resistance mechanism of Rifampicin (Rifampin or RIF), one of the more potent first-line drugs, might prove beneficial in predicting the consequence of an introduced mutation (which usually occur as single nucleotide polymorphisms or SNPs) and perhaps even overcome it using appropriate therapeutic interventions that improve RIF’s efficacy. To accomplish this task, models of acceptable quality were generated for the WT and clinically relevant, RIF resistance conferring, SNPs occurring at codon positions D516, H526 and S531 (E .coli numbering system) using MODELLER. The models were accordingly ranked using GA341 and z-DOPE score, and subsequently validated with QMEAN, PROCHECK and VERIFY3D. MD simulations spanning 100 ns were run for RIF-bound (complex) and RIF-free (holo) DNA-directed RNA polymerase (DDRP) protein systems for the WT and SNP mutants using GROMACS. The MD frames were analyzed using RMSD, Rg and RMSF. For further analysis, MD-TASK was used to analyze the calculated dynamic residue networks (DRNs) from the generated MD frames, determining both change in average shortest path (ΔL) and betweenness centrality (ΔBC). The RMSD analysis revealed that all of the SNP complex models displayed a level instability higher than that of the WT complex. A majority of the SNP complex models were also observed to have similar compactness to the WT holo when looking at the calculated Rg. The RMSF results also hinted towards possible physiological consequences of the mutations (generally referred to as a fitness cost) highlighted by the increased fluctuations of the zinc-binding domain and the MTB SI α helical coiled coil. For the first time, to the knowledge of the authors, DRN analysis was employed for the DDRP protein for both holo and complex systems, revealing insightful information about the residues that play a key role in the change in distance between residue pairs along with residues that play an essential role in protein communication within the calculated RIN. Overall, the data supported the conclusions drawn by a recent study that only concentrated on RIF-resistance in rpoB models which suggested that the binding pocket for the SNP models may result in the changed coordination of RIF which may be the main contributor to its impaired efficacy.
- Full Text:
- Authors: Monama, Mokgerwa Zacharia
- Date: 2020
- Subjects: Mycobacterium tuberculosis , Rifampin , Drug resistance , Homology (Biology) , Tuberculosis -- Chemotherapy
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/167508 , vital:41487
- Description: Tuberculosis or TB is an airborne disease caused by the non-motile bacilli, Mycobacterium tuberculosis (MTB). There are two main forms of TB, namely, latent TB or LTB, asymptomatic and non-contagious version which according to the World Health Organization (WHO) is estimated to afflict over a third of the world’s population; and active TB or ATB, a symptomatic and contagious version which continues to spread, affecting millions worldwide. With the already high reported prevalence of TB, the emergence of drug-resistant strains has prompted the development of novel approaches to enhance the efficacy of known drugs and a desperate search for novel compounds to combat MTB infections. It was for this very purpose that this study was conducted. A look into the resistance mechanism of Rifampicin (Rifampin or RIF), one of the more potent first-line drugs, might prove beneficial in predicting the consequence of an introduced mutation (which usually occur as single nucleotide polymorphisms or SNPs) and perhaps even overcome it using appropriate therapeutic interventions that improve RIF’s efficacy. To accomplish this task, models of acceptable quality were generated for the WT and clinically relevant, RIF resistance conferring, SNPs occurring at codon positions D516, H526 and S531 (E .coli numbering system) using MODELLER. The models were accordingly ranked using GA341 and z-DOPE score, and subsequently validated with QMEAN, PROCHECK and VERIFY3D. MD simulations spanning 100 ns were run for RIF-bound (complex) and RIF-free (holo) DNA-directed RNA polymerase (DDRP) protein systems for the WT and SNP mutants using GROMACS. The MD frames were analyzed using RMSD, Rg and RMSF. For further analysis, MD-TASK was used to analyze the calculated dynamic residue networks (DRNs) from the generated MD frames, determining both change in average shortest path (ΔL) and betweenness centrality (ΔBC). The RMSD analysis revealed that all of the SNP complex models displayed a level instability higher than that of the WT complex. A majority of the SNP complex models were also observed to have similar compactness to the WT holo when looking at the calculated Rg. The RMSF results also hinted towards possible physiological consequences of the mutations (generally referred to as a fitness cost) highlighted by the increased fluctuations of the zinc-binding domain and the MTB SI α helical coiled coil. For the first time, to the knowledge of the authors, DRN analysis was employed for the DDRP protein for both holo and complex systems, revealing insightful information about the residues that play a key role in the change in distance between residue pairs along with residues that play an essential role in protein communication within the calculated RIN. Overall, the data supported the conclusions drawn by a recent study that only concentrated on RIF-resistance in rpoB models which suggested that the binding pocket for the SNP models may result in the changed coordination of RIF which may be the main contributor to its impaired efficacy.
- Full Text:
A dynamics based analysis of allosteric modulation in heat shock proteins
- Authors: Penkler, David Lawrence
- Date: 2019
- Subjects: Heat shock proteins , Molecular chaperones , Allosteric regulation , Homeostasis , Protein kinases , Transcription factors , Adenosine triphosphatase , Cancer -- Chemotherapy , Molecular dynamics , High throughput screening (Drug development)
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/115948 , vital:34273
- Description: The 70 kDa and 90 kDa heat shock proteins (Hsp70 and Hsp90) are molecular chaperones that play central roles in maintaining cellular homeostasis in all organisms of life with the exception of archaea. In addition to their general chaperone function in protein quality control, Hsp70 and Hsp90 cooperate in the regulation and activity of some 200 known natively folded protein clients which include protein kinases, transcription factors and receptors, many of which are implicated as key regulators of essential signal transduction pathways. Both chaperones are considered to be large multi-domain proteins that rely on ATPase activity and co-chaperone interactions to regulate their conformational cycles for peptide binding and release. The unique positioning of Hsp90 at the crossroads of several fundamental cellular pathways coupled with its known association with diverse oncogenic peptide clients has brought the molecular chaperone under increasing interest as a potential anti-cancer target that is crucially implicated with all eight hallmarks of the disease. Current orthosteric drug discovery efforts aimed at the inhibition of the ATPase domain of Hsp90 have been limited due to high levels of associated toxicity. In an effort to circumnavigate this, the combined focus of research efforts is shifting toward alternative approaches such as interference with co-chaperone binding and the allosteric inhibition/activation of the molecular chaperone. The overriding aim of this thesis was to demonstrate how the computational technique of Perturbation response scanning (PRS) coupled with all-atom molecular dynamics simulations (MD) and dynamic residue interaction network (DRN) analysis can be used as a viable strategy to efficiently scan and accurately identify allosteric control element capable of modulating the functional dynamics of a protein. In pursuit of this goal, this thesis also contributes to the current understanding of the nucleotide dependent allosteric mechanisms at play in cellular functionality of both Hsp70 and Hsp90. All-atom MD simulations of E. coli DnaK provided evidence of nucleotide driven modulation of conformational dynamics in both the catalytically active and inactive states. PRS analysis employed on these trajectories demonstrated sensitivity toward bound nucleotide and peptide substrate, and provided evidence of a putative allosterically active intermediate state between the ATPase active and inactive conformational states. Simultaneous binding of ATP and peptide substrate was found to allosterically prime the chaperone for interstate conversion regardless of the transition direction. Detailed analysis of these allosterically primed states revealed select residue sites capable of selecting a coordinate shift towards the opposite conformational state. In an effort to validate these results, the predicted allosteric hot spot sites were cross-validated with known experimental works and found to overlap with functional sites implicated in allosteric signal propagation and ATPase activation in Hsp70. This study presented for the first time, the application of PRS as a suitable diagnostic tool for the elucidation and quantification of the allosteric potential of select residues to effect functionally relevant global conformational rearrangements. The PRS methodology described in this study was packaged within the Python programming environment in the MD-TASK software suite for command-line ease of use and made freely available. Homology modelling techniques were used to address the lack of experimental structural data for the human cytosolic isoform of Hsp90 and for the first time provided accurate full-length structural models of human Hsp90α in fully-closed and partially-open conformations. Long-range all-atom MD simulations of these structures revealed nucleotide driven modulation of conformational dynamics in Hsp90. Subsequent DRN and PRS analysis of these MD trajectories allowed for the quantification and elucidation of nucleotide driven allosteric modulation in the molecular chaperone. A detailed PRS analysis revealed allosteric inter-domain coupling between the extreme terminals of the chaperone in response to external force perturbations at either domain. Furthermore PRS also identified several individual residue sites that are capable of selecting conformational rearrangements towards functionally relevant states which may be considered to be putative allosteric target sites for future drug discovery efforts Molecular docking techniques were employed to investigate the modulation of conformational dynamics of human Hsp90α in response to ligand binding interactions at two identified allosteric sites at the C-terminal. High throughput screening of a small library of natural compounds indigenous to South Africa revealed three hit compounds at these sites: Cephalostatin 17, 20(29)-Lupene-3β isoferulate and 3'-Bromorubrolide F. All-atom MD simulations on these protein-ligand complexes coupled with DRN analysis and several advanced trajectory based analysis techniques provided evidence of selective allosteric modulation of Hsp90α conformational dynamics in response to the identity and location of the bound ligands. Ligands bound at the four-helix bundle presented as putative allosteric inhibitors of Hsp90α, driving conformational dynamics in favour of dimer opening and possibly dimer separation. Meanwhile, ligand interactions at an adjacent sub-pocket located near the interface between the middle and C-terminal domains demonstrated allosteric activation of the chaperone, modulating conformational dynamics in favour of the fully-closed catalytically active conformational state. Taken together, the data presented in this thesis contributes to the understanding of allosteric modulation of conformational dynamics in Hsp70 and Hsp90, and provides a suitable platform for future biochemical and drug discovery studies. Furthermore, the molecular docking and computational identification of allosteric compounds with suitable binding affinity for allosteric sites at the CTD of human Hsp90α provide for the first time “proof-of-principle” for the use of PRS in conjunction with MD simulations and DRN analysis as a suitable method for the rapid identification of allosteric sites in proteins that can be probed by small molecule interaction. The data presented in this section could pave the way for future allosteric drug discovery studies for the treatment of Hsp90 associated pathologies.
- Full Text:
- Authors: Penkler, David Lawrence
- Date: 2019
- Subjects: Heat shock proteins , Molecular chaperones , Allosteric regulation , Homeostasis , Protein kinases , Transcription factors , Adenosine triphosphatase , Cancer -- Chemotherapy , Molecular dynamics , High throughput screening (Drug development)
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/115948 , vital:34273
- Description: The 70 kDa and 90 kDa heat shock proteins (Hsp70 and Hsp90) are molecular chaperones that play central roles in maintaining cellular homeostasis in all organisms of life with the exception of archaea. In addition to their general chaperone function in protein quality control, Hsp70 and Hsp90 cooperate in the regulation and activity of some 200 known natively folded protein clients which include protein kinases, transcription factors and receptors, many of which are implicated as key regulators of essential signal transduction pathways. Both chaperones are considered to be large multi-domain proteins that rely on ATPase activity and co-chaperone interactions to regulate their conformational cycles for peptide binding and release. The unique positioning of Hsp90 at the crossroads of several fundamental cellular pathways coupled with its known association with diverse oncogenic peptide clients has brought the molecular chaperone under increasing interest as a potential anti-cancer target that is crucially implicated with all eight hallmarks of the disease. Current orthosteric drug discovery efforts aimed at the inhibition of the ATPase domain of Hsp90 have been limited due to high levels of associated toxicity. In an effort to circumnavigate this, the combined focus of research efforts is shifting toward alternative approaches such as interference with co-chaperone binding and the allosteric inhibition/activation of the molecular chaperone. The overriding aim of this thesis was to demonstrate how the computational technique of Perturbation response scanning (PRS) coupled with all-atom molecular dynamics simulations (MD) and dynamic residue interaction network (DRN) analysis can be used as a viable strategy to efficiently scan and accurately identify allosteric control element capable of modulating the functional dynamics of a protein. In pursuit of this goal, this thesis also contributes to the current understanding of the nucleotide dependent allosteric mechanisms at play in cellular functionality of both Hsp70 and Hsp90. All-atom MD simulations of E. coli DnaK provided evidence of nucleotide driven modulation of conformational dynamics in both the catalytically active and inactive states. PRS analysis employed on these trajectories demonstrated sensitivity toward bound nucleotide and peptide substrate, and provided evidence of a putative allosterically active intermediate state between the ATPase active and inactive conformational states. Simultaneous binding of ATP and peptide substrate was found to allosterically prime the chaperone for interstate conversion regardless of the transition direction. Detailed analysis of these allosterically primed states revealed select residue sites capable of selecting a coordinate shift towards the opposite conformational state. In an effort to validate these results, the predicted allosteric hot spot sites were cross-validated with known experimental works and found to overlap with functional sites implicated in allosteric signal propagation and ATPase activation in Hsp70. This study presented for the first time, the application of PRS as a suitable diagnostic tool for the elucidation and quantification of the allosteric potential of select residues to effect functionally relevant global conformational rearrangements. The PRS methodology described in this study was packaged within the Python programming environment in the MD-TASK software suite for command-line ease of use and made freely available. Homology modelling techniques were used to address the lack of experimental structural data for the human cytosolic isoform of Hsp90 and for the first time provided accurate full-length structural models of human Hsp90α in fully-closed and partially-open conformations. Long-range all-atom MD simulations of these structures revealed nucleotide driven modulation of conformational dynamics in Hsp90. Subsequent DRN and PRS analysis of these MD trajectories allowed for the quantification and elucidation of nucleotide driven allosteric modulation in the molecular chaperone. A detailed PRS analysis revealed allosteric inter-domain coupling between the extreme terminals of the chaperone in response to external force perturbations at either domain. Furthermore PRS also identified several individual residue sites that are capable of selecting conformational rearrangements towards functionally relevant states which may be considered to be putative allosteric target sites for future drug discovery efforts Molecular docking techniques were employed to investigate the modulation of conformational dynamics of human Hsp90α in response to ligand binding interactions at two identified allosteric sites at the C-terminal. High throughput screening of a small library of natural compounds indigenous to South Africa revealed three hit compounds at these sites: Cephalostatin 17, 20(29)-Lupene-3β isoferulate and 3'-Bromorubrolide F. All-atom MD simulations on these protein-ligand complexes coupled with DRN analysis and several advanced trajectory based analysis techniques provided evidence of selective allosteric modulation of Hsp90α conformational dynamics in response to the identity and location of the bound ligands. Ligands bound at the four-helix bundle presented as putative allosteric inhibitors of Hsp90α, driving conformational dynamics in favour of dimer opening and possibly dimer separation. Meanwhile, ligand interactions at an adjacent sub-pocket located near the interface between the middle and C-terminal domains demonstrated allosteric activation of the chaperone, modulating conformational dynamics in favour of the fully-closed catalytically active conformational state. Taken together, the data presented in this thesis contributes to the understanding of allosteric modulation of conformational dynamics in Hsp70 and Hsp90, and provides a suitable platform for future biochemical and drug discovery studies. Furthermore, the molecular docking and computational identification of allosteric compounds with suitable binding affinity for allosteric sites at the CTD of human Hsp90α provide for the first time “proof-of-principle” for the use of PRS in conjunction with MD simulations and DRN analysis as a suitable method for the rapid identification of allosteric sites in proteins that can be probed by small molecule interaction. The data presented in this section could pave the way for future allosteric drug discovery studies for the treatment of Hsp90 associated pathologies.
- Full Text:
Bioinformatics tool development with a focus on structural bioinformatics and the analysis of genetic variation in humans
- Authors: Brown, David K
- Date: 2018
- Subjects: Bioinformatics , Human genetics -- Variation , High performance computing , Workflow management systems , Molecular dynamics , Next generation sequencing , Human Mutation Analysis (HUMA)
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/60708 , vital:27820
- Description: This thesis is divided into three parts, united under the general theme of bioinformatics tool development and variation analysis. Part 1 describes the design and development of the Job Management System (JMS), a workflow management system for high performance computing (HPC). HPC has become an integral part of bioinformatics. Computational methods for molecular dynamics and next generation sequencing (NGS) analysis, which require complex calculations on large datasets, are not yet feasible on desktop computers. As such, powerful computer clusters have been employed to perform these calculations. However, making use of these HPC clusters requires familiarity with command line interfaces. This excludes a large number of researchers from taking advantage of these resources. JMS was developed as a tool to make it easier for researchers without a computer science background to make use of HPC. Additionally, JMS can be used to host computational tools and pipelines and generates both web-based interfaces and RESTful APIs for those tools. The web-based interfaces can be used to quickly and easily submit jobs to the underlying cluster. The RESTful web API, on the other hand, allows JMS to provided backend functionality for external tools and web servers that want to run jobs on the cluster. Numerous tools and workflows have already been added to JMS, several of which have been incorporated into external web servers. One such web server is the Human Mutation Analysis (HUMA) web server and database. HUMA, the topic of part 2 of this thesis, is a platform for the analysis of genetic variation in humans. HUMA aggregates data from various existing databases into a single, connected and related database. The advantages of this are realized in the powerful querying abilities that it provides. HUMA includes protein, gene, disease, and variation data and can be searched from the angle of any one of these categories. For example, searching for a protein will return the protein data (e.g. protein sequences, structures, domains and families, and other meta-data). However, the related nature of the database means that genes, diseases, variation, and literature related to the protein will also be returned, giving users a powerful and holistic view of all data associated with the protein. HUMA also provides links to the original sources of the data, allowing users to follow the links to find additional details. HUMA aims to be a platform for the analysis of genetic variation. As such, it also provides tools to visualize and analyse the data (several of which run on the underlying cluster, via JMS). These tools include alignment and 3D structure visualization, homology modeling, variant analysis, and the ability to upload custom variation datasets and map them to proteins, genes and diseases. HUMA also provides collaboration features, allowing users to share and discuss datasets and job results. Finally, part 3 of this thesis focused on the development of a suite of tools, MD-TASK, to analyse genetic variation at the protein structure level via network analysis of molecular dynamics simulations. The use of MD-TASK in combination with the tools developed in the previous parts of this thesis is showcased via the analysis of variation in the renin-angiotensinogen complex, a vital part of the renin-angiotensin system.
- Full Text:
- Authors: Brown, David K
- Date: 2018
- Subjects: Bioinformatics , Human genetics -- Variation , High performance computing , Workflow management systems , Molecular dynamics , Next generation sequencing , Human Mutation Analysis (HUMA)
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/60708 , vital:27820
- Description: This thesis is divided into three parts, united under the general theme of bioinformatics tool development and variation analysis. Part 1 describes the design and development of the Job Management System (JMS), a workflow management system for high performance computing (HPC). HPC has become an integral part of bioinformatics. Computational methods for molecular dynamics and next generation sequencing (NGS) analysis, which require complex calculations on large datasets, are not yet feasible on desktop computers. As such, powerful computer clusters have been employed to perform these calculations. However, making use of these HPC clusters requires familiarity with command line interfaces. This excludes a large number of researchers from taking advantage of these resources. JMS was developed as a tool to make it easier for researchers without a computer science background to make use of HPC. Additionally, JMS can be used to host computational tools and pipelines and generates both web-based interfaces and RESTful APIs for those tools. The web-based interfaces can be used to quickly and easily submit jobs to the underlying cluster. The RESTful web API, on the other hand, allows JMS to provided backend functionality for external tools and web servers that want to run jobs on the cluster. Numerous tools and workflows have already been added to JMS, several of which have been incorporated into external web servers. One such web server is the Human Mutation Analysis (HUMA) web server and database. HUMA, the topic of part 2 of this thesis, is a platform for the analysis of genetic variation in humans. HUMA aggregates data from various existing databases into a single, connected and related database. The advantages of this are realized in the powerful querying abilities that it provides. HUMA includes protein, gene, disease, and variation data and can be searched from the angle of any one of these categories. For example, searching for a protein will return the protein data (e.g. protein sequences, structures, domains and families, and other meta-data). However, the related nature of the database means that genes, diseases, variation, and literature related to the protein will also be returned, giving users a powerful and holistic view of all data associated with the protein. HUMA also provides links to the original sources of the data, allowing users to follow the links to find additional details. HUMA aims to be a platform for the analysis of genetic variation. As such, it also provides tools to visualize and analyse the data (several of which run on the underlying cluster, via JMS). These tools include alignment and 3D structure visualization, homology modeling, variant analysis, and the ability to upload custom variation datasets and map them to proteins, genes and diseases. HUMA also provides collaboration features, allowing users to share and discuss datasets and job results. Finally, part 3 of this thesis focused on the development of a suite of tools, MD-TASK, to analyse genetic variation at the protein structure level via network analysis of molecular dynamics simulations. The use of MD-TASK in combination with the tools developed in the previous parts of this thesis is showcased via the analysis of variation in the renin-angiotensinogen complex, a vital part of the renin-angiotensin system.
- Full Text:
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