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:
- Date Issued: 2020
- 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:
- Date Issued: 2020
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
- 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
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