List of Titles

Towards a possible future solution against Multidrug Resistance: An in silico exploration of the Multidrug and Toxic compound Extrusion (MATE) transporter proteins as potential antimicrobial drug targets

Authors: Damji, Amira Mahamood
Date: 2024-04-04
Subjects: Multidrug resistance , Multidrug and toxic compound extrusion family, eukaryotic , Docking , Molecular dynamics , Drug development , Transmembrane protein
Language: English
Type: Academic theses , Master's theses , text
Identifier: http://hdl.handle.net/10962/435009 , vital:73123
Description: The rise of multidrug resistance (MDR) has become a pressing global issue, hindering the treatment of cancers and infectious diseases, and imposing a burden on healthcare systems and the economy. The Multidrug and Toxic compound Extrusion (MATE) superfamily of membrane efflux transporters is one of the key players contributing to MDR due to their ability to export a wide range of cationic and hydrophilic xenobiotics, including treatment drugs, from cells, diminishing their efficacy. Targeting MATE transporters holds great promise in achieving some cellular control over MDR, but first, a deeper understanding of their structure-function-dynamics link is required. This study aimed to explore the MATE transporters as potential antimicrobial drug targets using a two-fold in silico approach. First, virtual screening of compounds from the South African Natural Compounds Database (SANCDB) was performed to identify prospective lead inhibitory compounds against the MATE transporters using molecular docking, and top hits were selected based on their binding energy and interaction with the active site on the N-lobe of the protein. Second, to investigate the molecular-level dynamics of their extrusion mechanism, the MATE transporter structures were embedded in a POPC membrane bilayer using the CHARMM-GUI online tool and then subjected to MD simulations for 100 ns with the CHARMM 36m force field using GROMACS. The resulting trajectories were evaluated using three standard metrics – RMSD, RMSF, and Rg; significant global structural changes were observed and key functional regions in both membrane- and non-membrane transmembrane (TM) segments were identified, containing more dynamic and flexible residues than other regions. Furthermore, the MATE transporters showed more of a loosely-packed structure, providing flexibility to allow for conformational switching during their substrate-transport cycle, which is typical for proteins whose secondary structures are composed of all α-helices. The scope of this study lied in the preliminary stages of the computer-aided drug design process, and provided insights that can be used to guide the development of strategies aimed at regulating or inhibiting the function of the MATE transporters, offering a possible future solution to the growing challenge of MDR. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2024
Full Text:
Date Issued: 2024-04-04

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

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

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

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

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

The characterization of GTP Cyclohydrolase I and 6-Pyruvoyl Tetrahydropterin Synthase enzymes as potential anti-malarial drug targets

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

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

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

Application of machine learning, molecular modelling and structural data mining against antiretroviral drug resistance in HIV-1

Authors: Sheik Amamuddy, Olivier Serge André
Date: 2020
Subjects: Machine learning , Molecules -- Models , Data mining , Neural networks (Computer science) , Antiretroviral agents , Protease inhibitors , Drug resistance , Multidrug resistance , Molecular dynamics , Renin-angiotensin system , HIV (Viruses) -- South Africa , HIV (Viruses) -- Social aspects -- South Africa , South African Natural Compounds Database
Language: English
Type: text , Thesis , Doctoral , PhD
Identifier: http://hdl.handle.net/10962/115964 , vital:34282
Description: Millions are affected with the Human Immunodeficiency Virus (HIV) world wide, even though the death toll is on the decline. Antiretrovirals (ARVs), more specifically protease inhibitors have shown tremendous success since their introduction into therapy since the mid 1990’s by slowing down progression to the Acquired Immune Deficiency Syndrome (AIDS). However, Drug Resistance Mutations (DRMs) are constantly selected for due to viral adaptation, making drugs less effective over time. The current challenge is to manage the infection optimally with a limited set of drugs, with differing associated levels of toxicities in the face of a virus that (1) exists as a quasispecies, (2) may transmit acquired DRMs to drug-naive individuals and (3) that can manifest class-wide resistance due to similarities in design. The presence of latent reservoirs, unawareness of infection status, education and various socio-economic factors make the problem even more complex. Adequate timing and choice of drug prescription together with treatment adherence are very important as drug toxicities, drug failure and sub-optimal treatment regimens leave room for further development of drug resistance. While CD4 cell count and the determination of viral load from patients in resource-limited settings are very helpful to track how well a patient’s immune system is able to keep the virus in check, they can be lengthy in determining whether an ARV is effective. Phenosense assay kits answer this problem using viruses engineered to contain the patient sequences and evaluating their growth in the presence of different ARVs, but this can be expensive and too involved for routine checks. As a cheaper and faster alternative, genotypic assays provide similar information from HIV pol sequences obtained from blood samples, inferring ARV efficacy on the basis of drug resistance mutation patterns. However, these are inherently complex and the various methods of in silico prediction, such as Geno2pheno, REGA and Stanford HIVdb do not always agree in every case, even though this gap decreases as the list of resistance mutations is updated. A major gap in HIV treatment is that the information used for predicting drug resistance is mainly computed from data containing an overwhelming majority of B subtype HIV, when these only comprise about 12% of the worldwide HIV infections. In addition to growing evidence that drug resistance is subtype-related, it is intuitive to hypothesize that as subtyping is a phylogenetic classification, the more divergent a subtype is from the strains used in training prediction models, the less their resistance profiles would correlate. For the aforementioned reasons, we used a multi-faceted approach to attack the virus in multiple ways. This research aimed to (1) improve resistance prediction methods by focusing solely on the available subtype, (2) mine structural information pertaining to resistance in order to find any exploitable weak points and increase knowledge of the mechanistic processes of drug resistance in HIV protease. Finally, (3) we screen for protease inhibitors amongst a database of natural compounds [the South African natural compound database (SANCDB)] to find molecules or molecular properties usable to come up with improved inhibition against the drug target. In this work, structural information was mined using the Anisotropic Network Model, Dynamics Cross-Correlation, Perturbation Response Scanning, residue contact network analysis and the radius of gyration. These methods failed to give any resistance-associated patterns in terms of natural movement, internal correlated motions, residue perturbation response, relational behaviour and global compaction respectively. Applications of drug docking, homology-modelling and energy minimization for generating features suitable for machine-learning were not very promising, and rather suggest that the value of binding energies by themselves from Vina may not be very reliable quantitatively. All these failures lead to a refinement that resulted in a highly sensitive statistically-guided network construction and analysis, which leads to key findings in the early dynamics associated with resistance across all PI drugs. The latter experiment unravelled a conserved lateral expansion motion occurring at the flap elbows, and an associated contraction that drives the base of the dimerization domain towards the catalytic site’s floor in the case of drug resistance. Interestingly, we found that despite the conserved movement, bond angles were degenerate. Alongside, 16 Artificial Neural Network models were optimised for HIV proteases and reverse transcriptase inhibitors, with performances on par with Stanford HIVdb. Finally, we prioritised 9 compounds with potential protease inhibitory activity using virtual screening and molecular dynamics (MD) to additionally suggest a promising modification to one of the compounds. This yielded another molecule inhibiting equally well both opened and closed receptor target conformations, whereby each of the compounds had been selected against an array of multi-drug-resistant receptor variants. While a main hurdle was a lack of non-B subtype data, our findings, especially from the statistically-guided network analysis, may extrapolate to a certain extent to them as the level of conservation was very high within subtype B, despite all the present variations. This network construction method lays down a sensitive approach for analysing a pair of alternate phenotypes for which complex patterns prevail, given a sufficient number of experimental units. During the course of research a weighted contact mapping tool was developed to compare renin-angiotensinogen variants and packaged as part of the MD-TASK tool suite. Finally the functionality, compatibility and performance of the MODE-TASK tool were evaluated and confirmed for both Python2.7.x and Python3.x, for the analysis of normals modes from single protein structures and essential modes from MD trajectories. These techniques and tools collectively add onto the conventional means of MD analysis.
Full Text:
Date Issued: 2020

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

Cyclooxygenase-1 as an anti-stroke target: potential inhibitor identification and non-synonymous single nucleotide polymorphism analysis

Authors: Muronzi, Tendai
Date: 2020
Subjects: Cerebrovascular disease , Cerebrovascular disease -- Treatment , Cerebrovascular disease -- Chemotherapy , Cyclooxygenases , High throughput screening (Drug development) , Drug development , Molecular dynamics , South African Natural Compounds Database , ZINC database
Language: English
Type: Thesis , Masters , MSc
Identifier: http://hdl.handle.net/10962/143404 , vital:38243
Description: Stroke is the third leading cause of death worldwide, with 87% of cases being ischemic stroke. The two primary therapeutic strategies to reduce post-ischemic brain damage are cellular and vascular approaches. The vascular strategy aims to rapidly re-open obstructed blood vessels, while the cellular approach aims to interfere with the signalling pathways that facilitate neuron damage and death. Unfortunately, popular vascular treatments have adverse side effects, necessitating the need for alternative chemotherapeutics. In this study, cyclooxygenase-1 (COX-1), which plays a significant role in the post- ischemic neuroinflammation and neuronal death, was targeted for identification of novel drug compounds and to assess the effect of nsSNPs on its structure and function. In a drug discovery part, ligands from the South African Natural Compounds Database (SANCDB-https://sancdb.rubi.ru.ac.za/) and ZINC database (http://zinc15.docking.org/) were used for high-throughput virtual screening (HVTS) against COX-1. Additionally, five nsSNPs were being investigated to assess their impact on protein structure and function. Three of these SNPs were in the COX-1 dimer interface. Molecular docking and molecular dynamics simulations revealed asymmetric nature of the protein. Several ligands, peculiar to each monomer, exhibited favourable binding energies in the respective active sites. SNP analysis indicated effects on inter-monomer interactions and protein stability.
Full Text:
Date Issued: 2020

Prediction of mass spectra for natural products using an ab initio approach

Authors: Novokoza, Yolanda
Date: 2020
Subjects: Molecular dynamics , Molecular dynamics -- Computer simulation , Mass spectroscopy , Electron impact ionization
Language: English
Type: text , Thesis , Masters , MSc
Identifier: http://hdl.handle.net/10962/167166 , vital:41443
Description: Mass spectrometry (MS) is a technique that measures the fragmentation of molecules, dependent on the molecule’s chemical composition and structure, by first introducing a charge on the molecules. The instrument records the mass to charge ratio, but the energy from the ionization process causes the molecule to fragment. The resultant mass spectrum is highly indicative of not only the molecule analyzed, but also its chemical composition. MS is used in research and industry for both routine and research purposes. One such way to ionize molecules for MS is by bombarding the molecule with electrons which is the basis of electron impact mass spectrometry (EIMS). Although EIMS is widely used, prediction of electron impact mass spectra from first principles is a challenging problem due to a need to accurately determine the probability of different fragmentation pathways of a molecule. Ab initio molecular dynamics based methods are able to explore in an automatic fashion the energetically available fragmentation paths thus give reaction mechanisms in an unbiased way. The mass spectra of five molecules have been explored in work-flows leading to the prediction of mass spectra. These molecules include three natural products alpha-hispanolol, PFB oxime derivative and boronolide (for which experimental mass spectra were not available) and two compounds from the NIST database (for which experimental mass spectra were available). For each of these systems many random conformations were generated using the RDKit library. To all conformations random velocities were applied to each atom. Ab initio molecular dynamics was performed on each conformer, using these initial random velocities using CP2K software, at DFTB+ level at a variety of highly raised temperatures (to accelerate the formation of fragments) Fragmentation was monitored by iterating through all bonds, and identifying bond breakages during dynamics. Graph theoretical packages were used then to track distinct fragments generated. For each of these fragments, charges were determined from Mulliken analysis for all atoms on the fragment from the QM calculations and sum of atomic spin densities per fragment was also plotted. The fragment with the greatest charge (corresponding to the formation of a cation fragment) was taken for plotting on the mass spectrum. Finally, from the mass of the fragment and its elemental composition, the isotopic distribution for the fragment was determined, and this distribution was included by addition in to the mass spectrum. For all trajectories, the sum of all isotopic distributions determined the final mass spectrum.
Full Text:
Date Issued: 2020

A dynamics based analysis of allosteric modulation in heat shock proteins

Authors: Penkler, David Lawrence
Date: 2019
Subjects: Heat shock proteins , Molecular chaperones , Allosteric regulation , Homeostasis , Protein kinases , Transcription factors , Adenosine triphosphatase , Cancer -- Chemotherapy , Molecular dynamics , High throughput screening (Drug development)
Language: English
Type: text , Thesis , Doctoral , PhD
Identifier: http://hdl.handle.net/10962/115948 , vital:34273
Description: The 70 kDa and 90 kDa heat shock proteins (Hsp70 and Hsp90) are molecular chaperones that play central roles in maintaining cellular homeostasis in all organisms of life with the exception of archaea. In addition to their general chaperone function in protein quality control, Hsp70 and Hsp90 cooperate in the regulation and activity of some 200 known natively folded protein clients which include protein kinases, transcription factors and receptors, many of which are implicated as key regulators of essential signal transduction pathways. Both chaperones are considered to be large multi-domain proteins that rely on ATPase activity and co-chaperone interactions to regulate their conformational cycles for peptide binding and release. The unique positioning of Hsp90 at the crossroads of several fundamental cellular pathways coupled with its known association with diverse oncogenic peptide clients has brought the molecular chaperone under increasing interest as a potential anti-cancer target that is crucially implicated with all eight hallmarks of the disease. Current orthosteric drug discovery efforts aimed at the inhibition of the ATPase domain of Hsp90 have been limited due to high levels of associated toxicity. In an effort to circumnavigate this, the combined focus of research efforts is shifting toward alternative approaches such as interference with co-chaperone binding and the allosteric inhibition/activation of the molecular chaperone. The overriding aim of this thesis was to demonstrate how the computational technique of Perturbation response scanning (PRS) coupled with all-atom molecular dynamics simulations (MD) and dynamic residue interaction network (DRN) analysis can be used as a viable strategy to efficiently scan and accurately identify allosteric control element capable of modulating the functional dynamics of a protein. In pursuit of this goal, this thesis also contributes to the current understanding of the nucleotide dependent allosteric mechanisms at play in cellular functionality of both Hsp70 and Hsp90. All-atom MD simulations of E. coli DnaK provided evidence of nucleotide driven modulation of conformational dynamics in both the catalytically active and inactive states. PRS analysis employed on these trajectories demonstrated sensitivity toward bound nucleotide and peptide substrate, and provided evidence of a putative allosterically active intermediate state between the ATPase active and inactive conformational states. Simultaneous binding of ATP and peptide substrate was found to allosterically prime the chaperone for interstate conversion regardless of the transition direction. Detailed analysis of these allosterically primed states revealed select residue sites capable of selecting a coordinate shift towards the opposite conformational state. In an effort to validate these results, the predicted allosteric hot spot sites were cross-validated with known experimental works and found to overlap with functional sites implicated in allosteric signal propagation and ATPase activation in Hsp70. This study presented for the first time, the application of PRS as a suitable diagnostic tool for the elucidation and quantification of the allosteric potential of select residues to effect functionally relevant global conformational rearrangements. The PRS methodology described in this study was packaged within the Python programming environment in the MD-TASK software suite for command-line ease of use and made freely available. Homology modelling techniques were used to address the lack of experimental structural data for the human cytosolic isoform of Hsp90 and for the first time provided accurate full-length structural models of human Hsp90α in fully-closed and partially-open conformations. Long-range all-atom MD simulations of these structures revealed nucleotide driven modulation of conformational dynamics in Hsp90. Subsequent DRN and PRS analysis of these MD trajectories allowed for the quantification and elucidation of nucleotide driven allosteric modulation in the molecular chaperone. A detailed PRS analysis revealed allosteric inter-domain coupling between the extreme terminals of the chaperone in response to external force perturbations at either domain. Furthermore PRS also identified several individual residue sites that are capable of selecting conformational rearrangements towards functionally relevant states which may be considered to be putative allosteric target sites for future drug discovery efforts Molecular docking techniques were employed to investigate the modulation of conformational dynamics of human Hsp90α in response to ligand binding interactions at two identified allosteric sites at the C-terminal. High throughput screening of a small library of natural compounds indigenous to South Africa revealed three hit compounds at these sites: Cephalostatin 17, 20(29)-Lupene-3β isoferulate and 3'-Bromorubrolide F. All-atom MD simulations on these protein-ligand complexes coupled with DRN analysis and several advanced trajectory based analysis techniques provided evidence of selective allosteric modulation of Hsp90α conformational dynamics in response to the identity and location of the bound ligands. Ligands bound at the four-helix bundle presented as putative allosteric inhibitors of Hsp90α, driving conformational dynamics in favour of dimer opening and possibly dimer separation. Meanwhile, ligand interactions at an adjacent sub-pocket located near the interface between the middle and C-terminal domains demonstrated allosteric activation of the chaperone, modulating conformational dynamics in favour of the fully-closed catalytically active conformational state. Taken together, the data presented in this thesis contributes to the understanding of allosteric modulation of conformational dynamics in Hsp70 and Hsp90, and provides a suitable platform for future biochemical and drug discovery studies. Furthermore, the molecular docking and computational identification of allosteric compounds with suitable binding affinity for allosteric sites at the CTD of human Hsp90α provide for the first time “proof-of-principle” for the use of PRS in conjunction with MD simulations and DRN analysis as a suitable method for the rapid identification of allosteric sites in proteins that can be probed by small molecule interaction. The data presented in this section could pave the way for future allosteric drug discovery studies for the treatment of Hsp90 associated pathologies.
Full Text:
Date Issued: 2019

Targeting allosteric sites of Escherichia coli heat shock protein 70 for antibiotic development

Authors: Okeke, Chiamaka Jessica
Date: 2019
Subjects: Heat shock proteins , Escherichia coli , Allosteric proteins , Antibiotics , Molecular chaperones , Ligands (Biochemistry) , Molecular dynamics , Principal components analysis , South African Natural Compounds Database
Language: English
Type: text , Thesis , Masters , MSc
Identifier: http://hdl.handle.net/10962/115998 , vital:34287
Description: Hsp70s are members of the heat shock proteins family with a molecular weight of 70-kDa and are the most abundant group in bacterial and eukaryotic systems, hence the most extensively studied ones. These proteins are molecular chaperones that play a significant role in protein homeostasis by facilitating appropriate folding of proteins, preventing proteins from aggregating and misfolding. They are also involved in translocation of proteins into subcellular compartments and protection of cells against stress. Stress caused by environmental or biological factors affects the functionality of the cell. In response to these stressful conditions, up-regulation of Hsp70s ensures that the cells are protected by balancing out unfolded proteins giving them ample time to repair denatured proteins. Hsp70s is connected to numerous illnesses such as autoimmune and neurodegenerative diseases, bacterial infection, cancer, malaria, and obesity. The multi-functional nature of Hsp70s predisposes them as promising therapeutic targets. Hsp70s play vital roles in various cell developments, and survival pathways, therefore targeting this protein will provide a new avenue towards the discovery of active therapeutic agents for the treatment of a wide range of diseases. Allosteric sites of these proteins in its multi-conformational states have not been explored for inhibitory properties hence the aim of this study. This study aims at identifying allosteric sites that inhibit the ATPase and substrate binding activities using computational approaches. Using E. coli as a model organism, molecular docking for high throughput virtual screening was carried out using 623 compounds from the South African Natural Compounds Database (SANCDB; https://sancdb.rubi.ru.ac.za/) against identified allosteric sites. Ligands with the highest binding affinity (good binders) interacting with critical allosteric residues that are druggable were identified. Molecular dynamics (MD) simulation was also performed on the identified hits to assess for protein-inhibitor complex stability. Finally, principal component analysis (PCA) was performed to understand the structural dynamics of the ligand-free and ligand-bound structures during MD simulation.
Full Text:
Date Issued: 2019

Bioinformatics tool development with a focus on structural bioinformatics and the analysis of genetic variation in humans

Authors: Brown, David K
Date: 2018
Subjects: Bioinformatics , Human genetics -- Variation , High performance computing , Workflow management systems , Molecular dynamics , Next generation sequencing , Human Mutation Analysis (HUMA)
Language: English
Type: text , Thesis , Doctoral , PhD
Identifier: http://hdl.handle.net/10962/60708 , vital:27820
Description: This thesis is divided into three parts, united under the general theme of bioinformatics tool development and variation analysis. Part 1 describes the design and development of the Job Management System (JMS), a workflow management system for high performance computing (HPC). HPC has become an integral part of bioinformatics. Computational methods for molecular dynamics and next generation sequencing (NGS) analysis, which require complex calculations on large datasets, are not yet feasible on desktop computers. As such, powerful computer clusters have been employed to perform these calculations. However, making use of these HPC clusters requires familiarity with command line interfaces. This excludes a large number of researchers from taking advantage of these resources. JMS was developed as a tool to make it easier for researchers without a computer science background to make use of HPC. Additionally, JMS can be used to host computational tools and pipelines and generates both web-based interfaces and RESTful APIs for those tools. The web-based interfaces can be used to quickly and easily submit jobs to the underlying cluster. The RESTful web API, on the other hand, allows JMS to provided backend functionality for external tools and web servers that want to run jobs on the cluster. Numerous tools and workflows have already been added to JMS, several of which have been incorporated into external web servers. One such web server is the Human Mutation Analysis (HUMA) web server and database. HUMA, the topic of part 2 of this thesis, is a platform for the analysis of genetic variation in humans. HUMA aggregates data from various existing databases into a single, connected and related database. The advantages of this are realized in the powerful querying abilities that it provides. HUMA includes protein, gene, disease, and variation data and can be searched from the angle of any one of these categories. For example, searching for a protein will return the protein data (e.g. protein sequences, structures, domains and families, and other meta-data). However, the related nature of the database means that genes, diseases, variation, and literature related to the protein will also be returned, giving users a powerful and holistic view of all data associated with the protein. HUMA also provides links to the original sources of the data, allowing users to follow the links to find additional details. HUMA aims to be a platform for the analysis of genetic variation. As such, it also provides tools to visualize and analyse the data (several of which run on the underlying cluster, via JMS). These tools include alignment and 3D structure visualization, homology modeling, variant analysis, and the ability to upload custom variation datasets and map them to proteins, genes and diseases. HUMA also provides collaboration features, allowing users to share and discuss datasets and job results. Finally, part 3 of this thesis focused on the development of a suite of tools, MD-TASK, to analyse genetic variation at the protein structure level via network analysis of molecular dynamics simulations. The use of MD-TASK in combination with the tools developed in the previous parts of this thesis is showcased via the analysis of variation in the renin-angiotensinogen complex, a vital part of the renin-angiotensin system.
Full Text:
Date Issued: 2018

In silico study of Plasmodium 1-deoxy-dxylulose 5-phosphate reductoisomerase (DXR) for identification of novel inhibitors from SANCDB

Authors: Diallo, Bakary N'tji
Date: 2018
Subjects: Plasmodium 1-deoxy-dxylulose 5-phosphate reductoisomerase , Isoprenoids , Plasmodium , Antimalarials , Malaria -- Chemotherapy , Molecules -- Models , Molecular dynamics , South African Natural Compounds Database
Language: English
Type: text , Thesis , Masters , MSc
Identifier: http://hdl.handle.net/10962/64012 , vital:28523
Description: Malaria remains a major health concern with a complex parasite constantly developing resistance to the different drugs introduced to treat it, threatening the efficacy of the current ACT treatment recommended by WHO (World Health Organization). Different antimalarial compounds with different mechanisms of action are ideal as this decreases chances of resistance occurring. Inhibiting DXR and consequently the MEP pathway is a good strategy to find a new antimalarial with a novel mode of action. From literature, all the enzymes of the MEP pathway have also been shown to be indispensable for the synthesis of isoprenoids. They have been validated as drug targets and the X-ray structure of each of the enzymes has been solved. DXR is a protein which catalyses the second step of the MEP pathway. There are currently 255 DXR inhibitors in the Binding Database (accessed November 2017) generally based on the fosmidomycin structural scaffold and thus often showing poor drug likeness properties. This study aims to research new DXR inhibitors using in silico techniques. We analysed the protein sequence and built 3D models in close and open conformations for the different Plasmodium sequences. Then SANCDB compounds were screened to identify new potential DXR inhibitors with new chemical scaffolds. Finally, the identified hits were submitted to molecular dynamics studies, preceded by a parameterization of the manganese atom in the protein active site.
Full Text:
Date Issued: 2018

The investigation of type-specific features of the copper coordinating AA9 proteins and their effect on the interaction with crystalline cellulose using molecular dynamics studies

Authors: Moses, Vuyani
Date: 2018
Subjects: Copper proteins , Cellulose , Molecular dynamics , Cellulose -- Biodegradation , Bioinformatics
Language: English
Type: text , Thesis , Doctoral , PhD
Identifier: http://hdl.handle.net/10962/58327 , vital:27230
Description: AA9 proteins are metallo-enzymes which are crucial for the early stages of cellulose degradation. AA9 proteins have been suggested to cleave glycosidic bonds linking cellulose through the use of their Cu2+ coordinating active site. AA9 proteins possess different regioselectivities depending on the resulting cleavage they form and as result, are grouped accordingly. Type 1 AA9 proteins cleave the C1 carbon of cellulose while Type 2 AA9 proteins cleave the C4 carbon and Type 3 AA9 proteins cleave either C1 or C4 carbons. The steric congestion of the AA9 active site has been proposed to be a contributor to the observed regioselectivity. As such, a bioinformatics characterisation of type-specific sequence and structural features was performed. Initially AA9 protein sequences were obtained from the Pfam database and multiple sequence alignment was performed. The sequences were phylogenetically characterised and sequences were grouped into their respective types and sub-groups were identified. A selection analysis was performed on AA9 LPMO types to determine the selective pressure acting on AA9 protein residues. Motif discovery was then performed to identify conserved sequence motifs in AA9 proteins. Once type-specific sequence features were identified structural mapping was performed to assess possible effects on substrate interaction. Physicochemical property analysis was also performed to assess biochemical differences between AA9 LPMO types. Molecular dynamics (MD) simulations were then employed to dynamically assess the consequences of the discovered type-specific features on AA9-cellulose interaction. Due to the absence of AA9 specific force field parameters MD simulations were not readily applicable. As a result, Potential Energy Surface (PES) scans were performed to evaluate the force field parameters for the AA9 active site using the PM6 semi empirical approach and least squares fitting. A Type 1 AA9 active site was constructed from the crystal structure 4B5Q, encompassing only the Cu2+ coordinating residues, the Cu2+ ion and two water residues. Due to the similarity in AA9 active sites, the Type force field parameters were validated on all three AA9 LPMO types. Two MD simulations for each AA9 LPMO types were conducted using two separate Lennard-Jones parameter sets. Once completed, the MD trajectories were analysed for various features including the RMSD, RMSF, radius of gyration, coordination during simulation, hydrogen bonding, secondary structure conservation and overall protein movement. Force field parameters were successfully evaluated and validated for AA9 proteins. MD simulations of AA9 proteins were able to reveal the presence of unique type-specific binding modes of AA9 active sites to cellulose. These binding modes were characterised by the presence of unique type-specific loops which were present in Type 2 and 3 AA9 proteins but not in Type 1 AA9 proteins. The loops were found to result in steric congestion that affects how the Cu2+ ion interacts with cellulose. As a result, Cu2+ binding to cellulose was observed for Type 1 and not Type 2 and 3 AA9 proteins. In this study force field parameters have been evaluated for the Type 1 active site of AA9 proteins and this parameters were evaluated on all three types and binding. Future work will focus on identifying the nature of the reactive oxygen species and performing QM/MM calculations to elucidate the reactive mechanism of all three AA9 LPMO types.
Full Text:
Date Issued: 2018

Structural studies on yeast eIF5A using biomolecular NMR and molecular dynamics

Authors: Sigauke, Lester Takunda
Date: 2015
Subjects: Molecular dynamics , Reverse transcriptase , HIV (Viruses) , HIV infections , Eukaryotic cells , Yeast
Language: English
Type: Thesis , Masters , MSc
Identifier: vital:4547 , http://hdl.handle.net/10962/d1017927
Description: Eukaryotic initiation factor 5A, eIF5A, is a ubiquitous eukaryotic protein that has been shown to influence the translation initiation of a specific subset of mRNAs. It is the only protein known to undergo hypusination in a two-step post translational modification process involving deoxyhypusine synthase (DHS) and deoxyhypusine hydroxylase (DOHH) enzymes. Hypusination has been shown to influence translation of HIV-1 and HTLV-1 nuclear export signals, while the involvement of active hypusinated eIF5A in induction of IRES mediated processes that initiate pro-apoptotic process have inspired studies into the manipulation of eIF5A in anti-cancer and anti-diabetic therapies. eIF5A oligomerisation in eukaryotic systems has been shown to be influenced by hypusination and the mechanism of dimerisation is RNA dependent. Nuclear magnetic resonance spectroscopy approaches were proposed to solve the structure of the hypusinated eIF5A in solution in order to understand the influence of hypusination on the monomeric arrangement which enhances dimerisation and activates the protein. Cleavage of the 18 kDa protein monomer by introduction of thrombin cleavage site within the flexible domain was thought to give rise to 10 kDa fragments accessible to a 600 MHz NMR spectrometer. Heteronuclear single quantum correlation experiments of the mutated isotopically labelled protein expressed in E. coli showed that the eIF5A protein with a thrombin cleavage insert, eIF5AThr (eIF5A subscript Thr), was unfolded. In silico investigations of the behaviour of eIF5A and eIF5AThr (eIF5A subscript Thr) models in solution using molecular dynamics showed that the mutated model had different solution dynamics to the native model. Chemical shift predictors were used to extract atomic resolution data of solution dynamics and the introduction of rigidity in the flexible loop region of eIF5A affected solution behaviour consistent with lack of in vivo function of eIF5AThr (eIF5A subscript Thr) in yeast. Residual dipolar coupling and T₁ relaxation times were calculated in anticipation of the extraction of experimental data from RDC and relaxation dispersion experiments based on HSQC measurable restraints.
Full Text:
Date Issued: 2015

Showing items 1 - 20 of 20

Towards a possible future solution against Multidrug Resistance: An in silico exploration of the Multidrug and Toxic compound Extrusion (MATE) transporter proteins as potential antimicrobial drug targets

In silico characterization of missense mutations in infectious diseases: case studies of tuberculosis and COVID-19

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

An in-silico study of the type II NADH: Quinone Oxidoreductase (ndh2). A new anti-malaria drug target

Identification of novel compounds against Plasmodium falciparum Cytochrome bc1 Complex inhibiting the trans-membrane electron transfer pathway: an In Silico study

Sequence, structure, dynamics, and substrate specificity analyses of bacterial Glycoside Hydrolase 1 enzymes from several activities

The characterization of GTP Cyclohydrolase I and 6-Pyruvoyl Tetrahydropterin Synthase enzymes as potential anti-malarial drug targets

Application of computer-aided drug design for identification of P. falciparum inhibitors

In silico identification of natural inhibitory compounds against the Mycobacterium tuberculosis Enzyme Pyrazinamidase using high-throughput virtual screening techniques

In silico identification of selective novel hits against the active site of wild type mycobacterium tuberculosis pyrazinamidase and its mutants

Application of machine learning, molecular modelling and structural data mining against antiretroviral drug resistance in HIV-1

Computer aided approaches against Human African Trypanosomiasis

Cyclooxygenase-1 as an anti-stroke target: potential inhibitor identification and non-synonymous single nucleotide polymorphism analysis

Prediction of mass spectra for natural products using an ab initio approach

A dynamics based analysis of allosteric modulation in heat shock proteins

Targeting allosteric sites of Escherichia coli heat shock protein 70 for antibiotic development

Bioinformatics tool development with a focus on structural bioinformatics and the analysis of genetic variation in humans

In silico study of Plasmodium 1-deoxy-dxylulose 5-phosphate reductoisomerase (DXR) for identification of novel inhibitors from SANCDB

The investigation of type-specific features of the copper coordinating AA9 proteins and their effect on the interaction with crystalline cellulose using molecular dynamics studies

Structural studies on yeast eIF5A using biomolecular NMR and molecular dynamics