- Title
- Structural analysis of effects of mutations on HIV-1 subtype C protease active site
- Creator
- Mathu, Alexander Muchugia Nganga
- Subject
- HIV (Viruses) -- Research
- Subject
- HIV infections -- Treatment -- Research
- Subject
- Protease inhibitors -- Research
- Subject
- Viruses -- Effect of drugs on -- Research
- Date Issued
- 2012
- Date
- 2012
- Type
- Thesis
- Type
- Masters
- Type
- MSc
- Identifier
- vital:4013
- Identifier
- http://hdl.handle.net/10962/d1004073
- Identifier
- HIV (Viruses) -- Research
- Identifier
- HIV infections -- Treatment -- Research
- Identifier
- Protease inhibitors -- Research
- Identifier
- Viruses -- Effect of drugs on -- Research
- Description
- HIV/AIDS is a global pandemic that poses a great threat especially in Sub-Saharan Africa where the highest population of those infected with the virus is found. It has far reaching medical, socio-economic and scientific implications. The HIV-1 protease enzyme is a prime therapeutic target that has been exploited in an effort to reduce morbidity and mortality. However problems arise from drug toxicity and drug-resistant mutations of the protease which is a motivation for research for new, safer and effective therapies. Evidence exists to show that there are significant genomic differences in Subtype B and C that have a negative effect on the intrinsic binding of inhibitors. It is imperative to look at all perspectives from epidemiological, molecular to the pharmacological ones so as to achieve rational design of therapeutic agents. This study involved the use of in silico structural analysis of the effects of mutations in the active site. The data was provided by the National Institute of Communicable Diseases consisting of HIV-1 Subtype C protease sequences of 29 infants exhibiting drug-resistance to ritonavir and lopinavir. The major active site mutations causing drug resistance identified in this study were M46I, I54V and V82A using the Stanford HIV database tool. Homology modeling without extra restraints produced models with improved quality in comparison to those with restraints. MetaMQAPII results differed when models were visualized as dimers giving erroneous modeled regions in comparison to monomers. A broader study with a larger dataset of HIV-1 subtype C protease sequences is required to increase statistical confidence and in order to identify the pattern of drug resistant mutations. Homology modeling without extra restraints is preferred for calculating homology models for the HIV-1 subtype C. Further investigations needs to be done to ascertain the accuracy of validation results for dimers from MetaMQAPII as it is designed for evaluation of monomers.
- Format
- 91 p.
- Format
- Publisher
- Rhodes University
- Publisher
- Faculty of Science, Biochemistry, Microbiology and Biotechnology
- Language
- English
- Rights
- Mathu, Alexander Muchugia Nganga
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Collections
RU Department of Biochemistry, Microbiology and Biotechnology (end of 2014)
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