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:
- Date Issued: 2023-10-13
- 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:
- Date Issued: 2023-10-13
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:
- Date Issued: 2023-10-13
- 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:
- Date Issued: 2023-10-13
An in-silico study of the type II NADH: Quinone Oxidoreductase (ndh2). A new anti-malaria drug target
- Authors: Baye, Bertha Cinthia
- Date: 2022-10-14
- Subjects: Malaria , Plasmodium , Molecular dynamics , Computer simulation , Quinone , Antimalarials , Molecules Models , Docking , Drugs Computer-aided design
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/365633 , vital:65767 , DOI https://doi.org/10.21504/10962/365633
- Description: Malaria is caused by Plasmodium parasites, spread to people through the bites of infected female Anopheles mosquitoes. This study focuses on all 5 (Plasmodium falciparum, Plasmodium knowlesi, Plasmodium malariae, Plasmodium ovale and Plasmodium vivax) parasites that cause malaria in humans. Africa is a developing continent, and it is the most affected with an estimation of 90% of more than 400 000 malaria-related deaths reported by the World Health Organization (WHO) report in 2020, in which 61% of that number are children under the ages of five. Malaria resistance was initially observed in early 1986 and with the progression of time anti-malarial drug resistance has only increased. As a result, there is a need to study the malarial proteins mechanism of action and identify alternative treatment strategies for this disease. Type II NADH: quinone oxidoreductase (NDH2) is a monotopic protein that catalyses the electron transfer from NADH to quinone via FAD without a proton-pumping activity, and functions as an initial enzyme, either in addition to or as an alternative to proton-pumping NADH dehydrogenase (complex I) in the respiratory chain of bacteria, archaea, and fungal and plant mitochondrial. The structures for the Plasmodium knowlesi, Plasmodium malariae, Plasmodium ovale and Plasmodium vivax were modelled from the crystal structure of Plasmodium falciparum (5JWA). Compounds from the South African natural compounds database (SANCDB) were docked against both the NDH2 crystal structure and modelled structures. By performing in silico screening the study aimed to find potential compounds that might interrupt the electron transfer to quinone therefore disturbing the enzyme‟s function and thereby possibly eliminating the plasmodium parasite. CHARMM-GUI was used to create the membrane (since this work is with membrane-bound proteins) and to orient the protein on the membrane using OPM server guidelines, the interface produced GROMACS topology files that were used in molecular dynamics simulations. Molecular dynamics simulations were performed in the Centre for high performance computing (CHPC) cluster under the CHEM0802 project and the trajectories produced were further analysed. In this work not only were hit compounds from SANCDB identified, but also differences in behaviour across species and in the presence or absence of the membrane were described. This highlights the need to include the correct protein environment when studying these systems. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
- Date Issued: 2022-10-14
- Authors: Baye, Bertha Cinthia
- Date: 2022-10-14
- Subjects: Malaria , Plasmodium , Molecular dynamics , Computer simulation , Quinone , Antimalarials , Molecules Models , Docking , Drugs Computer-aided design
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/365633 , vital:65767 , DOI https://doi.org/10.21504/10962/365633
- Description: Malaria is caused by Plasmodium parasites, spread to people through the bites of infected female Anopheles mosquitoes. This study focuses on all 5 (Plasmodium falciparum, Plasmodium knowlesi, Plasmodium malariae, Plasmodium ovale and Plasmodium vivax) parasites that cause malaria in humans. Africa is a developing continent, and it is the most affected with an estimation of 90% of more than 400 000 malaria-related deaths reported by the World Health Organization (WHO) report in 2020, in which 61% of that number are children under the ages of five. Malaria resistance was initially observed in early 1986 and with the progression of time anti-malarial drug resistance has only increased. As a result, there is a need to study the malarial proteins mechanism of action and identify alternative treatment strategies for this disease. Type II NADH: quinone oxidoreductase (NDH2) is a monotopic protein that catalyses the electron transfer from NADH to quinone via FAD without a proton-pumping activity, and functions as an initial enzyme, either in addition to or as an alternative to proton-pumping NADH dehydrogenase (complex I) in the respiratory chain of bacteria, archaea, and fungal and plant mitochondrial. The structures for the Plasmodium knowlesi, Plasmodium malariae, Plasmodium ovale and Plasmodium vivax were modelled from the crystal structure of Plasmodium falciparum (5JWA). Compounds from the South African natural compounds database (SANCDB) were docked against both the NDH2 crystal structure and modelled structures. By performing in silico screening the study aimed to find potential compounds that might interrupt the electron transfer to quinone therefore disturbing the enzyme‟s function and thereby possibly eliminating the plasmodium parasite. CHARMM-GUI was used to create the membrane (since this work is with membrane-bound proteins) and to orient the protein on the membrane using OPM server guidelines, the interface produced GROMACS topology files that were used in molecular dynamics simulations. Molecular dynamics simulations were performed in the Centre for high performance computing (CHPC) cluster under the CHEM0802 project and the trajectories produced were further analysed. In this work not only were hit compounds from SANCDB identified, but also differences in behaviour across species and in the presence or absence of the membrane were described. This highlights the need to include the correct protein environment when studying these systems. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
- Date Issued: 2022-10-14
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:
- Date Issued: 2022-10-14
- 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:
- Date Issued: 2022-10-14
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:
- Date Issued: 2022-04-08
- 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:
- Date Issued: 2022-04-08
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:
- Date Issued: 2022-04-08
- 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:
- Date Issued: 2022-04-08
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:
- Date Issued: 2021-10-29
- 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:
- Date Issued: 2021-10-29
In silico identification of natural inhibitory compounds against the Mycobacterium tuberculosis Enzyme Pyrazinamidase using high-throughput virtual screening techniques
- Authors: Kenyon, Thomas
- Date: 2021-10-29
- Subjects: Mycobacterium tuberculosis , Pyrazinamide , Molecular dynamics , High throughput screening (Drug development) , Mutagenesis , South African Natural Compounds database (SANCDB)
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10962/192074 , vital:45193
- Description: Tuberculosis (TB) is most commonly a pulmonary infection caused by the bacterium Mycobacterium tuberculosis. With the exception of the COVID-19 pandemic, TB was the most common cause of death due to an infectious disease for a number of years up until 2020. In 2019, 10 million people fell ill with TB worldwide and 1.4 million people died (WHO, 2020a). Additionally, multidrug-resistant TB (MDR-TB) remains a public health crisis and a health security threat. A global total of 206 030 people with multidrug- or rifampicin-resistant TB (MDR/RR-TB) were reported in 2019, a 10% increase from 186 883 in 2018. South Africa is ranked among the 48 high TB burden countries, with an estimated 360 000 people falling ill in 2019, resulting in 58 000 deaths, the majority of which being among people living with HIV. Unlike HIV, however, TB is a curable disease when managed correctly with long durations of antitubercular chemotherapy. Pyrazinamide (PZA) is an important first-line tuberculosis drug unique for its activity against latent TB. PZA is a prodrug, being converted into its active form, pyrazinoic acid (POA) by the Mtb gene pncA, coding for the pyrazinamidase enzyme (PZase). TB resistance to first-line drugs such as PZA is commonly associated with mutations in the pncA/PZase enzyme. This study aimed to identify potential novel inhibitors that bind to the active site of PZase. By making use of molecular docking studies and molecular dynamics (MD) simulations, high throughput virtual screening was performed on 623 compounds from the South African Natural Compounds database (SANCDB; https://sancdb.rubi.ru.ac.za). Ligands that selectively bound to the PZase active site were identified using docking studies, followed by MD simulations to assess ligand-PZase complex stability, Finally, hit compounds identified from the first round of MD simulations were screened again against PZase structures with high confidence point mutations known to infer PZA resistance in order to identify any novel compounds which had inhibitory potential against both WT and mutant forms of the PZase enzyme. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2021
- Full Text:
- Date Issued: 2021-10-29
- Authors: Kenyon, Thomas
- Date: 2021-10-29
- Subjects: Mycobacterium tuberculosis , Pyrazinamide , Molecular dynamics , High throughput screening (Drug development) , Mutagenesis , South African Natural Compounds database (SANCDB)
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10962/192074 , vital:45193
- Description: Tuberculosis (TB) is most commonly a pulmonary infection caused by the bacterium Mycobacterium tuberculosis. With the exception of the COVID-19 pandemic, TB was the most common cause of death due to an infectious disease for a number of years up until 2020. In 2019, 10 million people fell ill with TB worldwide and 1.4 million people died (WHO, 2020a). Additionally, multidrug-resistant TB (MDR-TB) remains a public health crisis and a health security threat. A global total of 206 030 people with multidrug- or rifampicin-resistant TB (MDR/RR-TB) were reported in 2019, a 10% increase from 186 883 in 2018. South Africa is ranked among the 48 high TB burden countries, with an estimated 360 000 people falling ill in 2019, resulting in 58 000 deaths, the majority of which being among people living with HIV. Unlike HIV, however, TB is a curable disease when managed correctly with long durations of antitubercular chemotherapy. Pyrazinamide (PZA) is an important first-line tuberculosis drug unique for its activity against latent TB. PZA is a prodrug, being converted into its active form, pyrazinoic acid (POA) by the Mtb gene pncA, coding for the pyrazinamidase enzyme (PZase). TB resistance to first-line drugs such as PZA is commonly associated with mutations in the pncA/PZase enzyme. This study aimed to identify potential novel inhibitors that bind to the active site of PZase. By making use of molecular docking studies and molecular dynamics (MD) simulations, high throughput virtual screening was performed on 623 compounds from the South African Natural Compounds database (SANCDB; https://sancdb.rubi.ru.ac.za). Ligands that selectively bound to the PZase active site were identified using docking studies, followed by MD simulations to assess ligand-PZase complex stability, Finally, hit compounds identified from the first round of MD simulations were screened again against PZase structures with high confidence point mutations known to infer PZA resistance in order to identify any novel compounds which had inhibitory potential against both WT and mutant forms of the PZase enzyme. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2021
- Full Text:
- Date Issued: 2021-10-29
In silico identification of selective novel hits against the active site of wild type mycobacterium tuberculosis pyrazinamidase and its mutants
- Authors: Gowo, Prudence
- Date: 2021-04
- Subjects: Mycobacterium tuberculosis , Pyrazinamide , Multidrug resistance , Antitubercular agents , Molecular dynamics , Hydrogen bonding , Ligand binding (Biochemistry) , Dynamic Residue Network
- Language: English
- Type: thesis , text , Masters , MSc
- Identifier: http://hdl.handle.net/10962/178007 , vital:42898
- Description: The World Health Organization declared Tuberculosis a global health emergency and has set a goal to eradicate it by 2035. However, effective treatment and control of the disease is being hindered by the emerging Multi-Drug Resistant and Extensively Drug Resistant strains on the most effective first line prodrug, Pyrazinamide (PZA). Studies have shown that the main cause of PZA resistance is due to mutations in the pncA gene that codes for the target protein Pyrazinamidase (PZase). Therefore, this study aimed to identify novel drug compounds that bind to the active site of wild type PZase and study the dynamics of these potential anti-TB drugs in the mutant systems of PZase. This approach will aid in identifying drugs that may be repurposed for TB therapy and/or designed to counteract PZA resistance. This was achieved by screening 2089 DrugBank compounds against the whole wild type (WT) PZase protein in molecular docking using AutoDOCK4.2. Compound screening based on docking binding energy, hydrogen bonds, molecular weight and active site proximity identified 47 compounds meeting all the set selection criteria. The stability of these compounds were analysed in Molecular Dynamic (MD) simulations and were further studied in PZase mutant systems of A3P, A134V, A146V, D8G, D49A, D49G, D63G, H51P, H137R, L85R, L116R, Q10P, R140S, T61P, V139M and Y103S. Generally, mutant-ligand systems displayed little deviation from the WT systems. The compound systems remained compact, with less fluctuations and more hydrogen bond interactions throughout the simulation (DB00255, DB00655, DB00672, DB00782, DB00977, DB01196, DB04573, DB06414, DB08981, DB11181, DB11760, DB13867, DB13952). From this research study, potential drugs that may be repurposed for TB therapy were identified. Majority of these drugs are currently used in the treatment of hypertension, menopause disorders and inflammation. To further understand the mutant-ligand dynamic systems, calculations such as Dynamic Residue Network (DRN) may be done. Also, the bioactivity of these drugs on Mycobacterium tuberculosis may be studied in wet laboratory, to understand their clinical impart in vivo experiments. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2021
- Full Text:
- Date Issued: 2021-04
- Authors: Gowo, Prudence
- Date: 2021-04
- Subjects: Mycobacterium tuberculosis , Pyrazinamide , Multidrug resistance , Antitubercular agents , Molecular dynamics , Hydrogen bonding , Ligand binding (Biochemistry) , Dynamic Residue Network
- Language: English
- Type: thesis , text , Masters , MSc
- Identifier: http://hdl.handle.net/10962/178007 , vital:42898
- Description: The World Health Organization declared Tuberculosis a global health emergency and has set a goal to eradicate it by 2035. However, effective treatment and control of the disease is being hindered by the emerging Multi-Drug Resistant and Extensively Drug Resistant strains on the most effective first line prodrug, Pyrazinamide (PZA). Studies have shown that the main cause of PZA resistance is due to mutations in the pncA gene that codes for the target protein Pyrazinamidase (PZase). Therefore, this study aimed to identify novel drug compounds that bind to the active site of wild type PZase and study the dynamics of these potential anti-TB drugs in the mutant systems of PZase. This approach will aid in identifying drugs that may be repurposed for TB therapy and/or designed to counteract PZA resistance. This was achieved by screening 2089 DrugBank compounds against the whole wild type (WT) PZase protein in molecular docking using AutoDOCK4.2. Compound screening based on docking binding energy, hydrogen bonds, molecular weight and active site proximity identified 47 compounds meeting all the set selection criteria. The stability of these compounds were analysed in Molecular Dynamic (MD) simulations and were further studied in PZase mutant systems of A3P, A134V, A146V, D8G, D49A, D49G, D63G, H51P, H137R, L85R, L116R, Q10P, R140S, T61P, V139M and Y103S. Generally, mutant-ligand systems displayed little deviation from the WT systems. The compound systems remained compact, with less fluctuations and more hydrogen bond interactions throughout the simulation (DB00255, DB00655, DB00672, DB00782, DB00977, DB01196, DB04573, DB06414, DB08981, DB11181, DB11760, DB13867, DB13952). From this research study, potential drugs that may be repurposed for TB therapy were identified. Majority of these drugs are currently used in the treatment of hypertension, menopause disorders and inflammation. To further understand the mutant-ligand dynamic systems, calculations such as Dynamic Residue Network (DRN) may be done. Also, the bioactivity of these drugs on Mycobacterium tuberculosis may be studied in wet laboratory, to understand their clinical impart in vivo experiments. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2021
- Full Text:
- Date Issued: 2021-04
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