Computer aided approaches against Human African Trypanosomiasis
- Authors: Kimuda, Magambo Phillip
- Date: 2020
- Subjects: African trypanosomiasis , African trypanosomiasis -- Chemotherapy , Genomics , Macrophage migration inhibitory factor , Trypanosoma brucei , Pteridines , Tetrahydrofolate dehydrogenase , Adenylic acid , Molecular dynamics , Principal components analysis , Bioinformatics , Single nucleotide polymorphisms , Single Nucleotide Variants , Candidate Gene Association Study (CGAS)
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/142542 , vital:38089
- Description: The thesis presented here is divided into two parts under a common theme that is the use of computer based tools, genomics, and in vitro experiments to develop innovative ways of tackling Human African Trypanosomiasis (HAT). Part I of this thesis focused on the human host genetic determinants while Part II focused on the discovery of novel chemotherapeutics against the parasite. Part I is further sub-divided into two parts: The first involves a Candidate Gene Association Study (CGAS) on an African population to identify genetic determinants associated with disease and/or susceptibility to HAT. The second involves studying the effects of missense Single Nucleotide Variants (SNVs) on protein structure, dynamics, and function using Macrophage Migration Inhibitory Factor (MIF) as a case study. Part II is also sub-divided into two parts: The first involves a computer based rational drug discovery of potential inhibitors against the Trypanosoma the folate pathway; particularly by targeting Trypanosoma brucei Pteridine Reductase (TbPTR1) which is an enzyme used by trypanosomes to overcome T. brucei Dihydrofolate Reductase (TbDHFR) inhibition. Lastly the derivation of CHARMM force-field parameters that can be used to accurately model the geometry and dynamics of the T. brucei Phosphodiesterase B1 enzyme (TbrPDEB1) bimetallic active site center. The derived parameters were then used in MD simulations to characterise protein-ligand residue interactions that are important in TbrPDEB1 inhibition with the goal of targeting the cyclic Adenosine Monophosphate (cAMP) signalling pathway. In the CGAS we were unable to detect any genetic associations in the Ugandan cohort analysed that passed correction for multiple testing in spite of the study being sufficiently powered. Additionally, our study found no association of the Apo lipoprotein 1 (APOL1) G2 allele association with protection against acute HAT that has been previously reported. Future investigations for example, Genome Wide Association Studies using larger samples sizes (>3000 cases and controls) are required. Macrophage migration inhibitory factor (MIF) is a cytokine that is important in both innate and adaptive immunity that has been shown to play a role in T. brucei pathogenicity using murine models. A total of 27 missense SNVs were modelled using homology modelling to create MIF protein mutants that were investigated using in silico effect prediction tools, molecular dynamics (MD), Principal Component Analysis (PCA), and Dynamic Residue Network (DRN) analysis. Our results demonstrate that mutations P2Q, I5M, P16Q, L23F, T24S, T31I, Y37H, H41P, M48V, P44L, G52C, S54R, I65M, I68T, S75F, N106S, and T113S caused significant conformational changes. Further, DRN analysis showed that residues P2, T31, Y37, G52, I65, I68, S75, N106, and T113S are part of a similar local residue interaction network with functional significance. These results show how polymorphisms such as missense SNVs can affect protein conformation, dynamics, and function. Trypanosomes are auxotrophic for folates and pterins but require them for survival. They scavenge them from their hosts. PTR1 is a multifunctional enzyme that is unique to trypanosomatids that reduces both pterins and folates. In the presence of DHFR inhibitors, PTR1 is over-expressed thus providing an escape from the effects of DHFR inhibition. Both TbPTR1 and TbDHFR are pharmacologically and genetically validated drug targets. In this study 5742 compounds were screened using molecular docking, and 13 promising binding modes were further analysed using MD simulations. The trajectories were analysed using RMSD, Rg, RMSF, PCA, Essential Dynamics Analysis (EDA), Molecular Mechanics Poisson–Boltzmann surface area (MM-PBSA) binding free energy calculations, and DRN analysis. The computational screening approach allowed us to identify five of the compounds, named RUBi004, RUBi007, RUBi014, RUBi016 and RUBi018 that exhibited antitrypanosomal growth activities against trypanosomes in culture with IC50 values of 12.5 ± 4.8 μM, 32.4 ± 4.2 μM, 5.9 ± 1.4 μM, 28.2 ± 3.3 μM, and 9.7 ± 2.1 μM, respectively. Further when used in combination with WR99210 a known TbDHFR inhibitor RUBi004, RUBi007, RUBi014 and RUBi018 showed antagonism while RUBi016 showed an additive effect. These results indicate that the four compounds might be competing with TbDHFR while RUBi016 might be more specific for TbPTR1. These compounds provide scaffolds that can be further optimised to improve their potency and specificity. Lastly, using a systematic approach we derived CHARMM force-field parameters to accurately describe the TbrPDEB1 bi-metal catalytic center. For dynamics, we employed mixed bonded and non-bonded approach. We optimised the structure using a two-layer QM/MM ONIOM (B3LYP/6-31(g): UFF). The TbrPDEB1 bi-metallic center bonds, angles, and dihedrals were parameterized by fitting the energy profiles from Potential Energy Surface (PES) scans to the CHARMM potential energy function. The parameters were validated by means of MD simulations and analysed using RMSD, Rg, RMSF, hydrogen bonding, bond/angle/dihedral evaluations, EDA, PCA, and DRN analysis. The force-field parameters were able to accurately reproduce the geometry and dynamics of the TbrPDEB1 bi-metal catalytic center during MD simulations. Molecular docking was used to identify 6 potential hits, that inhibited trypanosome growth in vitro. The derived force-field parameters were used to simulate the 6 protein-ligand complexes with the aim of elucidating crucial protein-ligand residue interactions. Using the most potent ligand RUBi022 that had an IC50 of 14.96 μM we were able to identify key residue interactions that can be of use in in silico prediction of potential TbrPDEB1 inhibitors. Overall we demonstrate how bioinformatics tools can complement current disease eradication strategies. Future work will focus on identifying variants identified in Genome Wide Association Studies and partnering with wet labs to carry out further enzyme-ligand activity relationship studies, structure determination or characterisation of appropriate protein-ligand complexes by crystallography, and site specific mutation studies
- Full Text:
- Date Issued: 2020
- Authors: Kimuda, Magambo Phillip
- Date: 2020
- Subjects: African trypanosomiasis , African trypanosomiasis -- Chemotherapy , Genomics , Macrophage migration inhibitory factor , Trypanosoma brucei , Pteridines , Tetrahydrofolate dehydrogenase , Adenylic acid , Molecular dynamics , Principal components analysis , Bioinformatics , Single nucleotide polymorphisms , Single Nucleotide Variants , Candidate Gene Association Study (CGAS)
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/142542 , vital:38089
- Description: The thesis presented here is divided into two parts under a common theme that is the use of computer based tools, genomics, and in vitro experiments to develop innovative ways of tackling Human African Trypanosomiasis (HAT). Part I of this thesis focused on the human host genetic determinants while Part II focused on the discovery of novel chemotherapeutics against the parasite. Part I is further sub-divided into two parts: The first involves a Candidate Gene Association Study (CGAS) on an African population to identify genetic determinants associated with disease and/or susceptibility to HAT. The second involves studying the effects of missense Single Nucleotide Variants (SNVs) on protein structure, dynamics, and function using Macrophage Migration Inhibitory Factor (MIF) as a case study. Part II is also sub-divided into two parts: The first involves a computer based rational drug discovery of potential inhibitors against the Trypanosoma the folate pathway; particularly by targeting Trypanosoma brucei Pteridine Reductase (TbPTR1) which is an enzyme used by trypanosomes to overcome T. brucei Dihydrofolate Reductase (TbDHFR) inhibition. Lastly the derivation of CHARMM force-field parameters that can be used to accurately model the geometry and dynamics of the T. brucei Phosphodiesterase B1 enzyme (TbrPDEB1) bimetallic active site center. The derived parameters were then used in MD simulations to characterise protein-ligand residue interactions that are important in TbrPDEB1 inhibition with the goal of targeting the cyclic Adenosine Monophosphate (cAMP) signalling pathway. In the CGAS we were unable to detect any genetic associations in the Ugandan cohort analysed that passed correction for multiple testing in spite of the study being sufficiently powered. Additionally, our study found no association of the Apo lipoprotein 1 (APOL1) G2 allele association with protection against acute HAT that has been previously reported. Future investigations for example, Genome Wide Association Studies using larger samples sizes (>3000 cases and controls) are required. Macrophage migration inhibitory factor (MIF) is a cytokine that is important in both innate and adaptive immunity that has been shown to play a role in T. brucei pathogenicity using murine models. A total of 27 missense SNVs were modelled using homology modelling to create MIF protein mutants that were investigated using in silico effect prediction tools, molecular dynamics (MD), Principal Component Analysis (PCA), and Dynamic Residue Network (DRN) analysis. Our results demonstrate that mutations P2Q, I5M, P16Q, L23F, T24S, T31I, Y37H, H41P, M48V, P44L, G52C, S54R, I65M, I68T, S75F, N106S, and T113S caused significant conformational changes. Further, DRN analysis showed that residues P2, T31, Y37, G52, I65, I68, S75, N106, and T113S are part of a similar local residue interaction network with functional significance. These results show how polymorphisms such as missense SNVs can affect protein conformation, dynamics, and function. Trypanosomes are auxotrophic for folates and pterins but require them for survival. They scavenge them from their hosts. PTR1 is a multifunctional enzyme that is unique to trypanosomatids that reduces both pterins and folates. In the presence of DHFR inhibitors, PTR1 is over-expressed thus providing an escape from the effects of DHFR inhibition. Both TbPTR1 and TbDHFR are pharmacologically and genetically validated drug targets. In this study 5742 compounds were screened using molecular docking, and 13 promising binding modes were further analysed using MD simulations. The trajectories were analysed using RMSD, Rg, RMSF, PCA, Essential Dynamics Analysis (EDA), Molecular Mechanics Poisson–Boltzmann surface area (MM-PBSA) binding free energy calculations, and DRN analysis. The computational screening approach allowed us to identify five of the compounds, named RUBi004, RUBi007, RUBi014, RUBi016 and RUBi018 that exhibited antitrypanosomal growth activities against trypanosomes in culture with IC50 values of 12.5 ± 4.8 μM, 32.4 ± 4.2 μM, 5.9 ± 1.4 μM, 28.2 ± 3.3 μM, and 9.7 ± 2.1 μM, respectively. Further when used in combination with WR99210 a known TbDHFR inhibitor RUBi004, RUBi007, RUBi014 and RUBi018 showed antagonism while RUBi016 showed an additive effect. These results indicate that the four compounds might be competing with TbDHFR while RUBi016 might be more specific for TbPTR1. These compounds provide scaffolds that can be further optimised to improve their potency and specificity. Lastly, using a systematic approach we derived CHARMM force-field parameters to accurately describe the TbrPDEB1 bi-metal catalytic center. For dynamics, we employed mixed bonded and non-bonded approach. We optimised the structure using a two-layer QM/MM ONIOM (B3LYP/6-31(g): UFF). The TbrPDEB1 bi-metallic center bonds, angles, and dihedrals were parameterized by fitting the energy profiles from Potential Energy Surface (PES) scans to the CHARMM potential energy function. The parameters were validated by means of MD simulations and analysed using RMSD, Rg, RMSF, hydrogen bonding, bond/angle/dihedral evaluations, EDA, PCA, and DRN analysis. The force-field parameters were able to accurately reproduce the geometry and dynamics of the TbrPDEB1 bi-metal catalytic center during MD simulations. Molecular docking was used to identify 6 potential hits, that inhibited trypanosome growth in vitro. The derived force-field parameters were used to simulate the 6 protein-ligand complexes with the aim of elucidating crucial protein-ligand residue interactions. Using the most potent ligand RUBi022 that had an IC50 of 14.96 μM we were able to identify key residue interactions that can be of use in in silico prediction of potential TbrPDEB1 inhibitors. Overall we demonstrate how bioinformatics tools can complement current disease eradication strategies. Future work will focus on identifying variants identified in Genome Wide Association Studies and partnering with wet labs to carry out further enzyme-ligand activity relationship studies, structure determination or characterisation of appropriate protein-ligand complexes by crystallography, and site specific mutation studies
- Full Text:
- Date Issued: 2020
Population genomics analysis of yellowfin tuna Thunnus albacares off South Africa reveals need for a shifted management boundary
- Authors: Mullins, Rachel Brenna
- Date: 2017
- Subjects: Yellowfin tuna fisheries -- South Africa -- Western Cape , Genomics , Tuna fisheries -- South Africa , Fishery management -- South Africa
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/57819 , vital:26992
- Description: Yellowfin tuna Thunnus albacares is a commercially and economically important fisheries species, which comprises the second largest component of South Africa’s catch of tuna and tuna-like species. Catches of the species off South Africa are treated as two discrete stocks by the two tuna Regional Fisheries Management Organisations (tRFMOs) under whose jurisdictions they fall. Individuals caught off the Western Cape, west of the boundary between the tRFMOs at 20°E, are included in assessment and management of the Atlantic Ocean yellowfin tuna stock by the International Commission for the Conservation of Atlantic Tunas (ICCAT), and those caught east of this boundary are assessed and managed as part of the Indian Ocean stock by the Indian Ocean Tuna Commission (IOTC). The boundary between these stocks is based on the confluence of the two oceans in this region and does not incorporate the population structure of species. For sustainable exploitation of fisheries resources, it is important that the definition of management stocks reflects species’ biological population structure; the fine-scale stock structure of yellowfin tuna off South Africa is therefore a research priority which this study aimed to address by means of population genomics analyses. Yellowfin tuna exhibit shallow genetic differentiation over wide geographic areas, and as such traditional population genetic approaches have limited power in resolving fishery significant population structure in the species. Herein, a population genomic approach was employed, specifically, genome-wide analysis of single nucleotide polymorphisms (SNPs) discovered using a next-generation DNA sequencing approach, to confer (i) increased statistical power to detect neutral structuring reflecting population connectivity patterns and (ii) signatures of local adaptation. The mitochondrial Control Region (mtDNA CR) was also sequenced to compare the resolving power of different approaches and to permit coalescent based analyses of the species evolutionary history in the region. Neutral SNP loci revealed significant structure within the dataset (Fst=0.0043; P<0.0001); partitioning of this differentiation within the dataset indicated significant differentiation between yellowfin tuna from the Western Cape and the Gulf of Guinea in the eastern Atlantic Ocean, with no significant differentiation between individuals from the Western Cape and Western Indian Ocean regions. This indicates two population units wherein there is a separation of the Gulf of Guinea from the remaining samples (Indian Ocean including Western Cape) that are largely derived from a single genetic population. This pattern was also supported by assignment tests. Positive outlier SNPs, exhibiting signatures of diversifying selection, suggest that individuals from these regions may be locally adapted, as well as demographically isolated. The mtDNA CR did not reveal any significant genetic structure among samples (Fst=0.0030; P=0.309), demonstrating the increased resolving power provided by population genomics approaches, but revealed signatures of historical demographic fluctuations associated with glacial cycles. Based on the findings of this study, it is suggested that yellowfin tuna caught off the Western Cape of South Africa are migrants from the Indian Ocean population, exhibiting significant genetic differentiation from the Atlantic Ocean Gulf of Guinea individuals, and should thus be included in the assessment and management of the Indian Ocean stock. It is therefore recommended that the boundary between the Atlantic and Indian Ocean yellowfin tuna stocks, under the mandates of ICCAT and the IOTC respectively, should be shifted to approximately 13.35°E to include all individuals caught in South African waters in the Indian Ocean stock.
- Full Text:
- Date Issued: 2017
- Authors: Mullins, Rachel Brenna
- Date: 2017
- Subjects: Yellowfin tuna fisheries -- South Africa -- Western Cape , Genomics , Tuna fisheries -- South Africa , Fishery management -- South Africa
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/57819 , vital:26992
- Description: Yellowfin tuna Thunnus albacares is a commercially and economically important fisheries species, which comprises the second largest component of South Africa’s catch of tuna and tuna-like species. Catches of the species off South Africa are treated as two discrete stocks by the two tuna Regional Fisheries Management Organisations (tRFMOs) under whose jurisdictions they fall. Individuals caught off the Western Cape, west of the boundary between the tRFMOs at 20°E, are included in assessment and management of the Atlantic Ocean yellowfin tuna stock by the International Commission for the Conservation of Atlantic Tunas (ICCAT), and those caught east of this boundary are assessed and managed as part of the Indian Ocean stock by the Indian Ocean Tuna Commission (IOTC). The boundary between these stocks is based on the confluence of the two oceans in this region and does not incorporate the population structure of species. For sustainable exploitation of fisheries resources, it is important that the definition of management stocks reflects species’ biological population structure; the fine-scale stock structure of yellowfin tuna off South Africa is therefore a research priority which this study aimed to address by means of population genomics analyses. Yellowfin tuna exhibit shallow genetic differentiation over wide geographic areas, and as such traditional population genetic approaches have limited power in resolving fishery significant population structure in the species. Herein, a population genomic approach was employed, specifically, genome-wide analysis of single nucleotide polymorphisms (SNPs) discovered using a next-generation DNA sequencing approach, to confer (i) increased statistical power to detect neutral structuring reflecting population connectivity patterns and (ii) signatures of local adaptation. The mitochondrial Control Region (mtDNA CR) was also sequenced to compare the resolving power of different approaches and to permit coalescent based analyses of the species evolutionary history in the region. Neutral SNP loci revealed significant structure within the dataset (Fst=0.0043; P<0.0001); partitioning of this differentiation within the dataset indicated significant differentiation between yellowfin tuna from the Western Cape and the Gulf of Guinea in the eastern Atlantic Ocean, with no significant differentiation between individuals from the Western Cape and Western Indian Ocean regions. This indicates two population units wherein there is a separation of the Gulf of Guinea from the remaining samples (Indian Ocean including Western Cape) that are largely derived from a single genetic population. This pattern was also supported by assignment tests. Positive outlier SNPs, exhibiting signatures of diversifying selection, suggest that individuals from these regions may be locally adapted, as well as demographically isolated. The mtDNA CR did not reveal any significant genetic structure among samples (Fst=0.0030; P=0.309), demonstrating the increased resolving power provided by population genomics approaches, but revealed signatures of historical demographic fluctuations associated with glacial cycles. Based on the findings of this study, it is suggested that yellowfin tuna caught off the Western Cape of South Africa are migrants from the Indian Ocean population, exhibiting significant genetic differentiation from the Atlantic Ocean Gulf of Guinea individuals, and should thus be included in the assessment and management of the Indian Ocean stock. It is therefore recommended that the boundary between the Atlantic and Indian Ocean yellowfin tuna stocks, under the mandates of ICCAT and the IOTC respectively, should be shifted to approximately 13.35°E to include all individuals caught in South African waters in the Indian Ocean stock.
- Full Text:
- Date Issued: 2017
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