Analysis of bacterial Mur amide ligase enzymes for the identification of inhibitory compounds by in silico methods
- Chamboko, Chiratidzo Respina
- Authors: Chamboko, Chiratidzo Respina
- Date: 2020
- Subjects: Mur amide ligases , Ligases , Ligand binding (Biochemistry) , Antibacterial agents
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/163430 , vital:41036
- Description: An increased emergence of resistant pathogenic bacterial strains over the years has resulted in many people dying of untreatable infections. This has become one of the most critical global public health problems, as resistant strains are complicating treatment of infectious diseases, increasing human morbidity, mortality, and health care costs. A very limited amount of effective antibiotics is currently available, but the development of novel classes of antibacterial agents is becoming a priority. Mur amide ligases are enzymes that have been identified as potentially good targets for antibiotics, as they are uniquely found in bacteria. They are responsible for the formation of peptide bonds in a growing peptidoglycan structure for bacterial cell walls. The current work presented here focused on characterizing these Mur amide ligase enzymes and obtaining inhibitory compounds that could potentially be of use in drug discovery of antibacterial agents. To do this, multiple sequence alignment, motif analysis and phylogenetic tree constructions were carried out, followed by docking studies and molecular dynamic simulations. Prior to docking, homology modelling of missing residues in the MurF structure (PDB 1GG4) was performed. Characterization results revealed the Mur amide ligase enzymes contained defined conservation in limited regions, that ultimately mapped towards the central domain responsible for ATP binding (presence of a conserved GKT motif). Further analysis of results further unraveled the unique patterns observed within each group of the family of enzymes. As a result of these findings, docking studies were carried out on each Mur amide ligase structure. At most, two ligands were identified to be sufficiently inhibiting each Mur amide ligase. The ligands obtained were SANC00574 and SANC00575 for MurC, SANC00290 and SANC00438 for MurD, SANC00290 and SANC00525 for MurE and SANC00290 and SANC00434 for MurF. The two best ligands identified for each enzyme had docked in the active site of their respective proteins, passed Lipinski’s rule of five and had substantially low binding energies. Molecular dynamic simulations were then performed to analyze the behavior of the proteins and protein-ligand complexes, to confirm the lead compounds as good inhibitors of the Mur amide ligases. In the case of MurC, MurD and MurE complexes, the identified ligands clearly impacted the behavior of the protein, as the ligand bound proteins became more compact and stable, while flexibility decreased. There was however an opposite effect on MurF complexes, that resulted in identified inhibitors being discarded. As a potential next step, in vivo and in vitro experiments can be performed with identified ligands from this research, to further support the information presented.
- Full Text:
- Authors: Chamboko, Chiratidzo Respina
- Date: 2020
- Subjects: Mur amide ligases , Ligases , Ligand binding (Biochemistry) , Antibacterial agents
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/163430 , vital:41036
- Description: An increased emergence of resistant pathogenic bacterial strains over the years has resulted in many people dying of untreatable infections. This has become one of the most critical global public health problems, as resistant strains are complicating treatment of infectious diseases, increasing human morbidity, mortality, and health care costs. A very limited amount of effective antibiotics is currently available, but the development of novel classes of antibacterial agents is becoming a priority. Mur amide ligases are enzymes that have been identified as potentially good targets for antibiotics, as they are uniquely found in bacteria. They are responsible for the formation of peptide bonds in a growing peptidoglycan structure for bacterial cell walls. The current work presented here focused on characterizing these Mur amide ligase enzymes and obtaining inhibitory compounds that could potentially be of use in drug discovery of antibacterial agents. To do this, multiple sequence alignment, motif analysis and phylogenetic tree constructions were carried out, followed by docking studies and molecular dynamic simulations. Prior to docking, homology modelling of missing residues in the MurF structure (PDB 1GG4) was performed. Characterization results revealed the Mur amide ligase enzymes contained defined conservation in limited regions, that ultimately mapped towards the central domain responsible for ATP binding (presence of a conserved GKT motif). Further analysis of results further unraveled the unique patterns observed within each group of the family of enzymes. As a result of these findings, docking studies were carried out on each Mur amide ligase structure. At most, two ligands were identified to be sufficiently inhibiting each Mur amide ligase. The ligands obtained were SANC00574 and SANC00575 for MurC, SANC00290 and SANC00438 for MurD, SANC00290 and SANC00525 for MurE and SANC00290 and SANC00434 for MurF. The two best ligands identified for each enzyme had docked in the active site of their respective proteins, passed Lipinski’s rule of five and had substantially low binding energies. Molecular dynamic simulations were then performed to analyze the behavior of the proteins and protein-ligand complexes, to confirm the lead compounds as good inhibitors of the Mur amide ligases. In the case of MurC, MurD and MurE complexes, the identified ligands clearly impacted the behavior of the protein, as the ligand bound proteins became more compact and stable, while flexibility decreased. There was however an opposite effect on MurF complexes, that resulted in identified inhibitors being discarded. As a potential next step, in vivo and in vitro experiments can be performed with identified ligands from this research, to further support the information presented.
- Full Text:
Analysis of bacterial Mur amide ligase enzymes for the identification of inhibitory compounds by in silico methods
- Chamboko, Chiratidzo Respina
- Authors: Chamboko, Chiratidzo Respina
- Date: 2020
- Subjects: Pathogenic microorganisms -- Analysis , Drug resistance in microorganisms , Microorganisms -- Effect of drugs on , Antibiotics -- Effectiveness , Pathogenic bacteria , Drug tolerance , Enzymes -- Analysis , Peptide antibiotics
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/161911 , vital:40690
- Description: An increased emergence of resistant pathogenic bacterial strains over the years has resulted in many people dying of untreatable infections. This has become one of the most critical global public health problems, as resistant strains are complicating treatment of infectious diseases, increasing human morbidity, mortality, and health care costs. A very limited amount of effective antibiotics is currently available, but the development of novel classes of antibacterial agents is becoming a priority. Mur amide ligases are enzymes that have been identified as potentially good targets for antibiotics, as they are uniquely found in bacteria. They are responsible for the formation of peptide bonds in a growing peptidoglycan structure for bacterial cell walls. The current work presented here focused on characterizing these Mur amide ligase enzymes and obtaining inhibitory compounds that could potentially be of use in drug discovery of antibacterial agents. To do this, multiple sequence alignment, motif analysis and phylogenetic tree constructions were carried out, followed by docking studies and molecular dynamic simulations. Prior to docking, homology modelling of missing residues in the MurF structure (PDB 1GG4) was performed. Characterization results revealed the Mur amide ligase enzymes contained defined conservation in limited regions, that ultimately mapped towards the central domain responsible for ATP binding (presence of a conserved GKT motif). Further analysis of results further unraveled the unique patterns observed within each group of the family of enzymes. As a result of these findings, docking studies were carried out on each Mur amide ligase structure. At most, two ligands were identified to be sufficiently inhibiting each Mur amide ligase. The ligands obtained were SANC00574 and SANC00575 for MurC, SANC00290 and SANC00438 for MurD, SANC00290 and SANC00525 for MurE and SANC00290 and SANC00434 for MurF. The two best ligands identified for each enzyme had docked in the active site of their respective proteins, passed Lipinski’s rule of five and had substantially low binding energies. Molecular dynamic simulations were then performed to analyze the behavior of the proteins and protein-ligand complexes, to confirm the lead compounds as good inhibitors of the Mur amide ligases. In the case of MurC, MurD and MurE complexes, the identified ligands clearly impacted the behavior of the protein, as the ligand bound proteins became more compact and stable, while flexibility decreased. There was however an opposite effect on MurF complexes, that resulted in identified inhibitors being discarded. As a potential next step, in vivo and in vitro experiments can be performed with identified ligands from this research, to further support the information presented.
- Full Text:
- Authors: Chamboko, Chiratidzo Respina
- Date: 2020
- Subjects: Pathogenic microorganisms -- Analysis , Drug resistance in microorganisms , Microorganisms -- Effect of drugs on , Antibiotics -- Effectiveness , Pathogenic bacteria , Drug tolerance , Enzymes -- Analysis , Peptide antibiotics
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/161911 , vital:40690
- Description: An increased emergence of resistant pathogenic bacterial strains over the years has resulted in many people dying of untreatable infections. This has become one of the most critical global public health problems, as resistant strains are complicating treatment of infectious diseases, increasing human morbidity, mortality, and health care costs. A very limited amount of effective antibiotics is currently available, but the development of novel classes of antibacterial agents is becoming a priority. Mur amide ligases are enzymes that have been identified as potentially good targets for antibiotics, as they are uniquely found in bacteria. They are responsible for the formation of peptide bonds in a growing peptidoglycan structure for bacterial cell walls. The current work presented here focused on characterizing these Mur amide ligase enzymes and obtaining inhibitory compounds that could potentially be of use in drug discovery of antibacterial agents. To do this, multiple sequence alignment, motif analysis and phylogenetic tree constructions were carried out, followed by docking studies and molecular dynamic simulations. Prior to docking, homology modelling of missing residues in the MurF structure (PDB 1GG4) was performed. Characterization results revealed the Mur amide ligase enzymes contained defined conservation in limited regions, that ultimately mapped towards the central domain responsible for ATP binding (presence of a conserved GKT motif). Further analysis of results further unraveled the unique patterns observed within each group of the family of enzymes. As a result of these findings, docking studies were carried out on each Mur amide ligase structure. At most, two ligands were identified to be sufficiently inhibiting each Mur amide ligase. The ligands obtained were SANC00574 and SANC00575 for MurC, SANC00290 and SANC00438 for MurD, SANC00290 and SANC00525 for MurE and SANC00290 and SANC00434 for MurF. The two best ligands identified for each enzyme had docked in the active site of their respective proteins, passed Lipinski’s rule of five and had substantially low binding energies. Molecular dynamic simulations were then performed to analyze the behavior of the proteins and protein-ligand complexes, to confirm the lead compounds as good inhibitors of the Mur amide ligases. In the case of MurC, MurD and MurE complexes, the identified ligands clearly impacted the behavior of the protein, as the ligand bound proteins became more compact and stable, while flexibility decreased. There was however an opposite effect on MurF complexes, that resulted in identified inhibitors being discarded. As a potential next step, in vivo and in vitro experiments can be performed with identified ligands from this research, to further support the information presented.
- Full Text:
Identification of SANCDB compounds against G2019S and I2020T variants of leucine-rich repeat Kinase 2 (LRRK2) for the development of drugs against Parkinson’s Disease
- Authors: Baye, Bertha Cinthia
- Date: 2020
- Subjects: Antiparkinsonian agents , Parkinson's disease -- Treatment , Protein kinases , Parkinson's disease -- Chemotherapy , Molecules -- Models
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/138764 , vital:37671
- Description: Parkinson’s disease is a type of movement disorder that occurs when nerve cells in the brain stop producing dopamine. It is the second neurodegenerative disease affecting 1-2% of people above the ages of 65 years old. There is a worldwide prevalence of 7 to 10 million affected people of all cultures and race. Studies have shown that mutation that causes Parkinson’s disease result in increased kinase activity. The c.6055 G > A in exon 41 is the most prevalent LRRK2 variation which causes a substitution of glycine to serine in G2019S in the highly activated loop of its MAP kinase domain. The LRRK2 G2019S variant is the most common genetic determinant of Parkinson’s disease identified to date. This work focused on building accurate 3D models of the LRRK2 kinase domain, that were used for large-scale in silico docking against South African natural compounds from the South African Natural Compounds Database (SANCDB; https://sancdb.rubi.ru.ac.za/). Molecular docking was performed to identify compounds that formed interactions with the active site of the protein and had the lowest binding energy scores. Molecular dynamics simulations showed different movements of the protein-ligand complexes and behavioural difference of the wildtype and the variants, all three structures proved to be compact. Network analysis was done to study residue interactions, contact maps, dynamic cross correlations, average BC and average L were used to study the residue interactions and general residue contribution to the functioning of the protein..
- Full Text:
- Authors: Baye, Bertha Cinthia
- Date: 2020
- Subjects: Antiparkinsonian agents , Parkinson's disease -- Treatment , Protein kinases , Parkinson's disease -- Chemotherapy , Molecules -- Models
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/138764 , vital:37671
- Description: Parkinson’s disease is a type of movement disorder that occurs when nerve cells in the brain stop producing dopamine. It is the second neurodegenerative disease affecting 1-2% of people above the ages of 65 years old. There is a worldwide prevalence of 7 to 10 million affected people of all cultures and race. Studies have shown that mutation that causes Parkinson’s disease result in increased kinase activity. The c.6055 G > A in exon 41 is the most prevalent LRRK2 variation which causes a substitution of glycine to serine in G2019S in the highly activated loop of its MAP kinase domain. The LRRK2 G2019S variant is the most common genetic determinant of Parkinson’s disease identified to date. This work focused on building accurate 3D models of the LRRK2 kinase domain, that were used for large-scale in silico docking against South African natural compounds from the South African Natural Compounds Database (SANCDB; https://sancdb.rubi.ru.ac.za/). Molecular docking was performed to identify compounds that formed interactions with the active site of the protein and had the lowest binding energy scores. Molecular dynamics simulations showed different movements of the protein-ligand complexes and behavioural difference of the wildtype and the variants, all three structures proved to be compact. Network analysis was done to study residue interactions, contact maps, dynamic cross correlations, average BC and average L were used to study the residue interactions and general residue contribution to the functioning of the protein..
- Full Text:
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