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
- 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
Sequence, structure, dynamics, and substrate specificity analyses of bacterial Glycoside Hydrolase 1 enzymes from several activities
- Authors: Veldman, Wayde Michael
- Date: 2022-04-08
- Subjects: Glycosidases , Bioinformatics , Molecular dynamics , Ligands (Biochemistry) , Enzymes , Ligand binding (Biochemistry) , Sequence alignment (Bioinformatics) , Structural bioinformatics
- Language: English
- Type: Doctoral thesis , text
- Identifier: http://hdl.handle.net/10962/233805 , vital:50129 , DOI 10.21504/10962/233810
- Description: Glycoside hydrolase 1 (GH1) enzymes are a ubiquitous family of enzymes that hydrolyse the glycosidic bond between two or more carbohydrates, or between a carbohydrate and a non-carbohydrate moiety. Despite their conserved catalytic domain, these enzymes have many different enzyme activities and/or substrate specificities as a change of only a few residues in the active site can alter their function. Most GH1 active site residues are situated in loop regions, and it is known that enzymes are more likely to develop new functions (broad specificity) if they possess an active site with a high proportion of loops. Furthermore, the GH1 active site consists of several subsites and cooperative binding makes the binding affinity of sites difficult to measure because the properties of one subsite are influenced by the binding of the other subsites. Extensive knowledge of protein-ligand interactions is critical to the comprehension of biology at the molecular level. However, the structural determinants and molecular details of GH1 ligand specificity and affinity are very broad, highly complex, not well understood, and therefore still need to be clarified. The aim of this study was to computationally characterise the activity of three newly solved GH1 crystallographic structures sent to us by our collaborators, and to provide evidence for their ligand-binding specificities. In addition, the differences in structural and biochemical contributions to enzyme specificity and/or function between different GH1 activities/enzymes was assessed, and the sequence/structure/function relationship of several activities of GH1 enzymes was analysed and compared. To accomplish the research aims, sequence analyses involving sequence identity, phylogenetics, and motif discovery were performed. As protein structure is more conserved than sequence, the discovered motifs were mapped to 3D structures for structural analysis and comparisons. To obtain information on enzyme mechanism or mode of action, as well as structure-function relationship, computational methods such as docking, molecular dynamics, binding free energy calculations, and essential dynamics were implemented. These computational approaches can provide information on the active site, binding residues, protein-ligand interactions, binding affinity, conformational change, and most structural or dynamic elements that play a role in enzyme function. The three new structures received from our collaborators are the first GH1 crystallographic structures from Bacillus licheniformis ever determined. As phospho-glycoside compounds were unavailable for purchase for use in activity assays, and as the active sites of the structures were absent of ligand, in silico docking and MD simulations were performed to provide evidence for their GH1 activities and substrate specificities. First though, the amino acid sequences of all known characterised bacterial GH1 enzymes were retrieved from the CAZy database and compared to the sequences of the three new B. licheniformis crystallographic structures which provided evidence of the putative 6Pβ-glucosidase activity of enzyme BlBglH, and dual 6Pβ-glucosidase/6Pβ-galactosidase (dual-phospho) activity of enzymes BlBglB and BlBglC. As all three enzymes were determined to be putative 6Pβ-glycosidase activity enzymes, much of the thesis focused on the overall analysis and comparison of the 6Pβ-glucosidase, 6Pβ-galactosidase, and dual-phospho activities that make up the 6Pβ-glycosidases. The 6Pβ-glycosidase active site residues were identified through consensus of binding interactions using all known 6Pβ-glycosidase PDB structures complexed complete ligand substrates. With regards to the 6Pβ-glucosidase activity, it was found that the L8b loop is longer and forms extra interactions with the L8a loop likely leading to increased L8 loop rigidity which would prevent the displacement of residue Ala423 ensuring a steric clash with galactoconfigured ligands and may engender substrate specificity for gluco-configured ligands only. Also, during molecular dynamics simulations using enzyme BlBglH (6Pβ-glucosidase activity), it was revealed that the favourable binding of substrate stabilises the loops that surround and make up the enzyme active site. Using the BlBglC (dual-phospho activity) enzyme structure with either galacto- (PNP6Pgal) or gluco-configured (PNP6Pglc) ligands, MD simulations in triplicate revealed important details of the broad specificity of dual-phospho activity enzymes. The ligand O4 hydroxyl position is the only difference between PNP6Pgal and PNP6Pgal, and it was found that residues Gln23 and Trp433 bind strongly to the ligand O3 hydroxyl group in the PNP6Pgal-enzyme complex, but to the ligand O4 hydroxyl group in the PNP6Pglc-enzyme complex. Also, His124 formed many hydrogen bonds with the PNP6Pgal O3 hydroxyl group but had none with PNP6Pglc. Alternatively, residues Tyr173, Tyr301, Gln302 and Thr321 formed hydrogen bonds with PNP6Pglc but not PNP6Pgal. Lastly, using multiple 3D structures from various GH1 activities, a large network of conserved interactions between active site residues (and other important residues) was uncovered, which most likely stabilise the loop regions that contain these residues, helping to retain their positions needed for binding molecules. Alternatively, there exists several differing residue-residue interactions when comparing each of the activities which could contribute towards individual activity substrate specificity by causing slightly different overall structure and malleability of the active site. Altogether, the findings in this thesis shed light on the function, mechanisms, dynamics, and ligand-binding of GH1 enzymes – particularly of the 6Pβ-glycosidase activities. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
- Date Issued: 2022-04-08
- Authors: Veldman, Wayde Michael
- Date: 2022-04-08
- Subjects: Glycosidases , Bioinformatics , Molecular dynamics , Ligands (Biochemistry) , Enzymes , Ligand binding (Biochemistry) , Sequence alignment (Bioinformatics) , Structural bioinformatics
- Language: English
- Type: Doctoral thesis , text
- Identifier: http://hdl.handle.net/10962/233805 , vital:50129 , DOI 10.21504/10962/233810
- Description: Glycoside hydrolase 1 (GH1) enzymes are a ubiquitous family of enzymes that hydrolyse the glycosidic bond between two or more carbohydrates, or between a carbohydrate and a non-carbohydrate moiety. Despite their conserved catalytic domain, these enzymes have many different enzyme activities and/or substrate specificities as a change of only a few residues in the active site can alter their function. Most GH1 active site residues are situated in loop regions, and it is known that enzymes are more likely to develop new functions (broad specificity) if they possess an active site with a high proportion of loops. Furthermore, the GH1 active site consists of several subsites and cooperative binding makes the binding affinity of sites difficult to measure because the properties of one subsite are influenced by the binding of the other subsites. Extensive knowledge of protein-ligand interactions is critical to the comprehension of biology at the molecular level. However, the structural determinants and molecular details of GH1 ligand specificity and affinity are very broad, highly complex, not well understood, and therefore still need to be clarified. The aim of this study was to computationally characterise the activity of three newly solved GH1 crystallographic structures sent to us by our collaborators, and to provide evidence for their ligand-binding specificities. In addition, the differences in structural and biochemical contributions to enzyme specificity and/or function between different GH1 activities/enzymes was assessed, and the sequence/structure/function relationship of several activities of GH1 enzymes was analysed and compared. To accomplish the research aims, sequence analyses involving sequence identity, phylogenetics, and motif discovery were performed. As protein structure is more conserved than sequence, the discovered motifs were mapped to 3D structures for structural analysis and comparisons. To obtain information on enzyme mechanism or mode of action, as well as structure-function relationship, computational methods such as docking, molecular dynamics, binding free energy calculations, and essential dynamics were implemented. These computational approaches can provide information on the active site, binding residues, protein-ligand interactions, binding affinity, conformational change, and most structural or dynamic elements that play a role in enzyme function. The three new structures received from our collaborators are the first GH1 crystallographic structures from Bacillus licheniformis ever determined. As phospho-glycoside compounds were unavailable for purchase for use in activity assays, and as the active sites of the structures were absent of ligand, in silico docking and MD simulations were performed to provide evidence for their GH1 activities and substrate specificities. First though, the amino acid sequences of all known characterised bacterial GH1 enzymes were retrieved from the CAZy database and compared to the sequences of the three new B. licheniformis crystallographic structures which provided evidence of the putative 6Pβ-glucosidase activity of enzyme BlBglH, and dual 6Pβ-glucosidase/6Pβ-galactosidase (dual-phospho) activity of enzymes BlBglB and BlBglC. As all three enzymes were determined to be putative 6Pβ-glycosidase activity enzymes, much of the thesis focused on the overall analysis and comparison of the 6Pβ-glucosidase, 6Pβ-galactosidase, and dual-phospho activities that make up the 6Pβ-glycosidases. The 6Pβ-glycosidase active site residues were identified through consensus of binding interactions using all known 6Pβ-glycosidase PDB structures complexed complete ligand substrates. With regards to the 6Pβ-glucosidase activity, it was found that the L8b loop is longer and forms extra interactions with the L8a loop likely leading to increased L8 loop rigidity which would prevent the displacement of residue Ala423 ensuring a steric clash with galactoconfigured ligands and may engender substrate specificity for gluco-configured ligands only. Also, during molecular dynamics simulations using enzyme BlBglH (6Pβ-glucosidase activity), it was revealed that the favourable binding of substrate stabilises the loops that surround and make up the enzyme active site. Using the BlBglC (dual-phospho activity) enzyme structure with either galacto- (PNP6Pgal) or gluco-configured (PNP6Pglc) ligands, MD simulations in triplicate revealed important details of the broad specificity of dual-phospho activity enzymes. The ligand O4 hydroxyl position is the only difference between PNP6Pgal and PNP6Pgal, and it was found that residues Gln23 and Trp433 bind strongly to the ligand O3 hydroxyl group in the PNP6Pgal-enzyme complex, but to the ligand O4 hydroxyl group in the PNP6Pglc-enzyme complex. Also, His124 formed many hydrogen bonds with the PNP6Pgal O3 hydroxyl group but had none with PNP6Pglc. Alternatively, residues Tyr173, Tyr301, Gln302 and Thr321 formed hydrogen bonds with PNP6Pglc but not PNP6Pgal. Lastly, using multiple 3D structures from various GH1 activities, a large network of conserved interactions between active site residues (and other important residues) was uncovered, which most likely stabilise the loop regions that contain these residues, helping to retain their positions needed for binding molecules. Alternatively, there exists several differing residue-residue interactions when comparing each of the activities which could contribute towards individual activity substrate specificity by causing slightly different overall structure and malleability of the active site. Altogether, the findings in this thesis shed light on the function, mechanisms, dynamics, and ligand-binding of GH1 enzymes – particularly of the 6Pβ-glycosidase activities. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
- Date Issued: 2022-04-08
Molecular simulations of potential agents and targets of Alzheimer’s disease
- Authors: Joli, Luxolo
- Date: 2020
- Subjects: Alzheimer's disease -- Chemotherapy , Alzheimer's disease -- Treatment , Ligands (Biochemistry) , Proteins -- Chemistry , Molecular dynamics -- Simulation methods
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/146411 , vital:38523
- Description: Alzheimer's Disease (AD) is a neurodegenerative brain disorder that was first discovered in 1901 by Dr Aloïs Alzheimer and was later reported publicly in 1906. The German doctor had a 51-yearold woman patient called Auguste Deter, who was suffering from a rare brain disorder with early signs of memory loss and cognition. Alzheimer's Disease is the most common type of dementia that affects people with the age of 65 years and older. There is no single known cause of Alzheimer’s disease however, amyloid β-peptide (Aβ1–40/42) was found to be at the centre of AD pathogenesis and this connection was referred as “amyloid hypothesis”. It is suspected that an accumulation of amyloid β-peptide is a major contributor to neuronal dysfunction and degeneration. Alzheimer’s disease is complex and therefore, currently there is no medication available that treats the disease. However, there are approaches that focus on helping people maintain mental function, manage behavioral symptoms, and slow down the symptoms of disease. According to South Africa’s 2011 census, there are approximately 2.2 million people in South Africa with some form of dementia and therefore there is a need to find a treatment for the disease. This study aims to find agents and targets of Alzheimer’s Disease by using different computational techniques such as molecular modelling. The study will use compounds from the South African Compounds Database (SANCDB) and the following therapeutic targets α-, β- and γ-secretase, acetylcholinesterase, tau protein and neprilysin. A successful High-throughput Virtual Screening (HTVS) study to determine lead compounds was performed using a computational program called KNIME. Molecular docking was achieved with GLIDE as it allows for exhaustive ligand flexibility. The docking calculations were carried out using the high level of precision XP (extra precision) for enhanced docking accuracy. The binding affinities (docking scores) for the best bound ligands obtained from docking were in the order of -5 kcal/mol or less. The ligandSANC00370 was the best binding ligand against the protein 1J1C_B and had the best binding energy of -13.94 kcal/mol compared to others. The receptor-ligand complexes were analyzed using the interaction diagrams obtained from the Discovery Studio Visualizer and Maestro programs. Molecular Dynamics simulations were performed on the complexes obtained from docking to help in optimizing their interactions. The simulations were performed using the Desmond tool with the OPLS3 force field. 100 ns simulations were performed for six systems with the best docking score results epresenting each of the therapeutic targets and for the other complex systems, 50 ns simulations were performed. The Desmond simulations were analyzed using the Simulations Interaction Diagrams such as PL-RMSD, L-RMSF, P-RMSF, L-Torsions, P-SSE, LP-Contacts and L-Properties. Maestro was used to visualize the stability of the ligands in the active site during the simulation. All 13 Desmond simulations were successful however, there were 9 simulations which produced satisfactory results while the others were nsatisfactory. Based on the molecular docking and Molecular Dynamics results of this study, 9 potential targets and 6 potential agents were obtained successfully and can be studied further as therapeutics for Alzheimer’s Disease.
- Full Text:
- Date Issued: 2020
- Authors: Joli, Luxolo
- Date: 2020
- Subjects: Alzheimer's disease -- Chemotherapy , Alzheimer's disease -- Treatment , Ligands (Biochemistry) , Proteins -- Chemistry , Molecular dynamics -- Simulation methods
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/146411 , vital:38523
- Description: Alzheimer's Disease (AD) is a neurodegenerative brain disorder that was first discovered in 1901 by Dr Aloïs Alzheimer and was later reported publicly in 1906. The German doctor had a 51-yearold woman patient called Auguste Deter, who was suffering from a rare brain disorder with early signs of memory loss and cognition. Alzheimer's Disease is the most common type of dementia that affects people with the age of 65 years and older. There is no single known cause of Alzheimer’s disease however, amyloid β-peptide (Aβ1–40/42) was found to be at the centre of AD pathogenesis and this connection was referred as “amyloid hypothesis”. It is suspected that an accumulation of amyloid β-peptide is a major contributor to neuronal dysfunction and degeneration. Alzheimer’s disease is complex and therefore, currently there is no medication available that treats the disease. However, there are approaches that focus on helping people maintain mental function, manage behavioral symptoms, and slow down the symptoms of disease. According to South Africa’s 2011 census, there are approximately 2.2 million people in South Africa with some form of dementia and therefore there is a need to find a treatment for the disease. This study aims to find agents and targets of Alzheimer’s Disease by using different computational techniques such as molecular modelling. The study will use compounds from the South African Compounds Database (SANCDB) and the following therapeutic targets α-, β- and γ-secretase, acetylcholinesterase, tau protein and neprilysin. A successful High-throughput Virtual Screening (HTVS) study to determine lead compounds was performed using a computational program called KNIME. Molecular docking was achieved with GLIDE as it allows for exhaustive ligand flexibility. The docking calculations were carried out using the high level of precision XP (extra precision) for enhanced docking accuracy. The binding affinities (docking scores) for the best bound ligands obtained from docking were in the order of -5 kcal/mol or less. The ligandSANC00370 was the best binding ligand against the protein 1J1C_B and had the best binding energy of -13.94 kcal/mol compared to others. The receptor-ligand complexes were analyzed using the interaction diagrams obtained from the Discovery Studio Visualizer and Maestro programs. Molecular Dynamics simulations were performed on the complexes obtained from docking to help in optimizing their interactions. The simulations were performed using the Desmond tool with the OPLS3 force field. 100 ns simulations were performed for six systems with the best docking score results epresenting each of the therapeutic targets and for the other complex systems, 50 ns simulations were performed. The Desmond simulations were analyzed using the Simulations Interaction Diagrams such as PL-RMSD, L-RMSF, P-RMSF, L-Torsions, P-SSE, LP-Contacts and L-Properties. Maestro was used to visualize the stability of the ligands in the active site during the simulation. All 13 Desmond simulations were successful however, there were 9 simulations which produced satisfactory results while the others were nsatisfactory. Based on the molecular docking and Molecular Dynamics results of this study, 9 potential targets and 6 potential agents were obtained successfully and can be studied further as therapeutics for Alzheimer’s Disease.
- Full Text:
- Date Issued: 2020
- «
- ‹
- 1
- ›
- »