Inhibitor search and variant analysis of Acetylcholinesterase
- Authors: Ras, Harnaud
- Date: 2021-04
- Subjects: Acetylcholinesterase , Alzheimer's disease , Acetylcholinesterase -- Inhibitors , Alzheimer's disease -- Chemotherapy , Cerebrovascular disease -- Treatment , Molecular mechanics Poisson–Boltzmann surface area (MM-PBSA)
- Language: English
- Type: thesis , text , Masters , MSc
- Identifier: http://hdl.handle.net/10962/178191 , vital:42919
- Description: Acetylcholinesterase (AChE) inhibition is used to treat Alzheimer's disease by increasing the availability of acetylcholine to carry nerve signals in the brain. The response to this treatment varies widely, which may be due to altered affnity to the current drugs caused by genetic variation. Various negative side-effects limit their use. As this is one of the only available therapeutic drug targets to treat Alzheimer's disease, decreasing the negative effects is of great importance. AChE is involved in biological processes that occur after acute ischemic stroke. Stroke is the third leading cause of death worldwide, and 87% of all stroke cases belong to ischemic stroke. AchEI (cholinesterase inhibitors) have been suggested to have properties that lower the risk of stroke. AChE is one of 15 verified drug targets under study for treatment of stroke. In addition to Alzheimer's disease and stroke, Lewy body disease (LBD) may be treated using cholinesterase inhibitors. The goals of this study are to find inhibitors that can potentially be used to treat Alzheimer's disease and/or stroke and to investigate variants which may affect protein dynamics and function. Two variants were analyzed, P247L and T229S. Molecular simulation of the P247L variant resulted in a disruption in protein dynamics in comparison to the wildtype. A total of 5728 molecules were screened and 10 nanosecond simulations were used to narrow down the set of compounds. The four best performing molecules were simulated for 10 nanoseconds. MM-PBSA was performed to identify molecules with high binding free energies. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2021
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- Date Issued: 2021-04
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.
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- Date Issued: 2020