In silico characterization of missense mutations in infectious diseases: case studies of tuberculosis and COVID-19
- Authors: Barozi, Victor
- Date: 2023-10-13
- Subjects: Uncatalogued
- 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: Uncatalogued
- 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
Prediction of mass spectra using an ab initio approach
- Authors: Novokoza, Yolanda
- Date: 2023-10-13
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/${Handle} , vital:72818
- Description: Access restricted. Expected release date in 2025. , Thesis (PhD) -- Faculty of Science, Chemistry, 2023
- Full Text:
- Date Issued: 2023-10-13
- Authors: Novokoza, Yolanda
- Date: 2023-10-13
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/${Handle} , vital:72818
- Description: Access restricted. Expected release date in 2025. , Thesis (PhD) -- Faculty of Science, Chemistry, 2023
- Full Text:
- Date Issued: 2023-10-13
The heterologous expression and in vitro biochemical characterization of the Hsp70 escort protein 1 and mitochondrial Hsp70 partner proteins of the Trypanosoma brucei parasite and humans
- Authors: Mahlalela, Maduma Ernst
- Date: 2023-10-13
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/431832 , vital:72807 , DOI 10.21504/10962/431832
- Description: The 70 kDa family of heat shock proteins (Hsp70) plays a central role in the maintenance of cellular proteostasis, with paralogues occurring in all the major compartments of the eukaryotic cell. Hsp70s act in conjunction with proteins known as co-chaperones, as part of the larger molecular chaperone network. In the mitochondrion, Hsp70 (mtHsp70) is responsible for the import of proteins synthesized in the cytosol, protein folding in the matrix and the maintenance of the iron-sulphur cluster. In human cells mtHsp70 (HSPA9) is also referred to as mortalin, as the knockdown of the protein leads to cell mortality. Trypanosoma brucei is the causative agent of sleeping sickness in humans and nagana in animals. In the T. brucei parasite there are three identical mtHsp70 (TbmtHsp70) proteins that are produced, forming part of the Hsp70 machinery that is essential for parasite survival. In humans, the levels of HSPA9 are often elevated in non-communicable diseases such as cancer and neurodegeneration. Despite their vital cellular roles, mtHsp70s are characteristically prone to self-aggregation. The binding of the Hsp70 escort protein (Hep1) is required to prevent the aggregation of mtHsp70 proteins, enabling the proteins to function. In many non-communicable diseases, mtHsp70 and other molecular chaperones such as heat shock protein 90 (Hsp90) are being investigated as potential drug targets. Existing anti-trypanosomal drugs for treating sleeping sickness are toxic, having adverse side effects that are potentially lethal. Investigations into Hsp70s, and other molecular chaperones, form part of the research into the discovery of novel and efficacious therapeutics. This is the first study to characterise Hep1 and investigate its partnership with mtHsp70 in T. brucei. The overall aim of this study was to comparatively assess the T. brucei and human mtHsp70/Hep1 partnerships. The putative T. brucei Hep1 (TbHep1) orthologue was analysed in silico, and it was found to possess a zinc finger domain consisting of anti-parallel β-sheets that are characteristic of canonical Hep1 proteins, whilst the N-terminal domain was unstructured. Based on sequence analysis, the regions outside of the zinc finger domains lacked conservation. Despite the lack of sequence conservation, the N- and C-terminal regions of TbHep1 shared segments of similarity with Hep1 orthologues of other kinetoplastid and trypanosomal orthologues. The same held true for the N- and C-termini of human Hep1 (HsHep1) when compared to other Hep1 orthologues of mammalian origin. Biochemical analysis revealed TbmtHsp70 and HSPA9 to be prone to self-aggregation, which was reduced by co-expression with TbHep1 and HsHep1, respectively. Recently Hep1 proteins have been determined to be present in the cytosol. In this study, TbHep1 and HsHep1 also interacted with the cytosolic Hsp70s, HSPA1A and TbHsp70, by preventing their thermally induced aggregation and stimulating their ATPase activities. TbHep1 and HsHep1 also suppressed the thermally induced aggregation of the model substrates malate dehydrogenase and citrate synthase, independently of Hsp70. To date, only two Hep1 orthologues, HsHep1 and LbHep1, have been found to function in a similar manner to a J-protein co-chaperone by stimulating the ATPase activities of their partner mtHsp70 proteins. In this study, TbHep1 stimulated the ATPase activity of TbmtHsp70. HsHep1 also stimulated the ATPase activity of TbmtHsp70. However, the mechanism of action still needs to be determined. This study also explored the potential of the Hep1 orthologues to be functionally activated by oxidative stress, which is prevalent in mitochondria. The abilities of TbHep1 and HsHep1 to reduce the thermally induced aggregation of malate dehydrogenase were enhanced under oxidative conditions. Disrupting the function of Hep1 has been found to eventually lead to cell death, and given the critical role played by mtHsp70 in the cell, this partnership could be exploited as a potential drug target. In conclusion, this study demonstrated that TbHep1 and HsHep1 functionally interact with mtHsp70s, whilst also possessing independent chaperone activities that are also potentially influenced by the environmental redox state. , Thesis (PhD) -- Faculty of Science, Biotechnology Innovation Centre, 2023
- Full Text:
- Date Issued: 2023-10-13
- Authors: Mahlalela, Maduma Ernst
- Date: 2023-10-13
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/431832 , vital:72807 , DOI 10.21504/10962/431832
- Description: The 70 kDa family of heat shock proteins (Hsp70) plays a central role in the maintenance of cellular proteostasis, with paralogues occurring in all the major compartments of the eukaryotic cell. Hsp70s act in conjunction with proteins known as co-chaperones, as part of the larger molecular chaperone network. In the mitochondrion, Hsp70 (mtHsp70) is responsible for the import of proteins synthesized in the cytosol, protein folding in the matrix and the maintenance of the iron-sulphur cluster. In human cells mtHsp70 (HSPA9) is also referred to as mortalin, as the knockdown of the protein leads to cell mortality. Trypanosoma brucei is the causative agent of sleeping sickness in humans and nagana in animals. In the T. brucei parasite there are three identical mtHsp70 (TbmtHsp70) proteins that are produced, forming part of the Hsp70 machinery that is essential for parasite survival. In humans, the levels of HSPA9 are often elevated in non-communicable diseases such as cancer and neurodegeneration. Despite their vital cellular roles, mtHsp70s are characteristically prone to self-aggregation. The binding of the Hsp70 escort protein (Hep1) is required to prevent the aggregation of mtHsp70 proteins, enabling the proteins to function. In many non-communicable diseases, mtHsp70 and other molecular chaperones such as heat shock protein 90 (Hsp90) are being investigated as potential drug targets. Existing anti-trypanosomal drugs for treating sleeping sickness are toxic, having adverse side effects that are potentially lethal. Investigations into Hsp70s, and other molecular chaperones, form part of the research into the discovery of novel and efficacious therapeutics. This is the first study to characterise Hep1 and investigate its partnership with mtHsp70 in T. brucei. The overall aim of this study was to comparatively assess the T. brucei and human mtHsp70/Hep1 partnerships. The putative T. brucei Hep1 (TbHep1) orthologue was analysed in silico, and it was found to possess a zinc finger domain consisting of anti-parallel β-sheets that are characteristic of canonical Hep1 proteins, whilst the N-terminal domain was unstructured. Based on sequence analysis, the regions outside of the zinc finger domains lacked conservation. Despite the lack of sequence conservation, the N- and C-terminal regions of TbHep1 shared segments of similarity with Hep1 orthologues of other kinetoplastid and trypanosomal orthologues. The same held true for the N- and C-termini of human Hep1 (HsHep1) when compared to other Hep1 orthologues of mammalian origin. Biochemical analysis revealed TbmtHsp70 and HSPA9 to be prone to self-aggregation, which was reduced by co-expression with TbHep1 and HsHep1, respectively. Recently Hep1 proteins have been determined to be present in the cytosol. In this study, TbHep1 and HsHep1 also interacted with the cytosolic Hsp70s, HSPA1A and TbHsp70, by preventing their thermally induced aggregation and stimulating their ATPase activities. TbHep1 and HsHep1 also suppressed the thermally induced aggregation of the model substrates malate dehydrogenase and citrate synthase, independently of Hsp70. To date, only two Hep1 orthologues, HsHep1 and LbHep1, have been found to function in a similar manner to a J-protein co-chaperone by stimulating the ATPase activities of their partner mtHsp70 proteins. In this study, TbHep1 stimulated the ATPase activity of TbmtHsp70. HsHep1 also stimulated the ATPase activity of TbmtHsp70. However, the mechanism of action still needs to be determined. This study also explored the potential of the Hep1 orthologues to be functionally activated by oxidative stress, which is prevalent in mitochondria. The abilities of TbHep1 and HsHep1 to reduce the thermally induced aggregation of malate dehydrogenase were enhanced under oxidative conditions. Disrupting the function of Hep1 has been found to eventually lead to cell death, and given the critical role played by mtHsp70 in the cell, this partnership could be exploited as a potential drug target. In conclusion, this study demonstrated that TbHep1 and HsHep1 functionally interact with mtHsp70s, whilst also possessing independent chaperone activities that are also potentially influenced by the environmental redox state. , Thesis (PhD) -- Faculty of Science, Biotechnology Innovation Centre, 2023
- Full Text:
- Date Issued: 2023-10-13
Wildlife-vehicle collisions mitigation measures using road ecological data and deep learning
- Authors: Nandutu, Irene
- Date: 2023-10-13
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/431907 , vital:72814
- Description: Access restricted. Expected release in 2025. , Thesis (PhD) -- Faculty of Science, Mathematics, 2023
- Full Text:
- Date Issued: 2023-10-13
- Authors: Nandutu, Irene
- Date: 2023-10-13
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/431907 , vital:72814
- Description: Access restricted. Expected release in 2025. , Thesis (PhD) -- Faculty of Science, Mathematics, 2023
- Full Text:
- Date Issued: 2023-10-13
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