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Characterizing drug resistance using geometric ensembles from HIV protease dynamics

View ORCID ProfileOlivier Sheik Amamuddy, View ORCID ProfileNigel T. Bishop, View ORCID ProfileÖzlem Tastan Bishop
doi: https://doi.org/10.1101/379958
Olivier Sheik Amamuddy
1Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa
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  • ORCID record for Olivier Sheik Amamuddy
Nigel T. Bishop
2Department of Mathematics (Pure & Applied), Rhodes University, Grahamstown 6140, South Africa
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Özlem Tastan Bishop
1Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa
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  • For correspondence: o.tastanbishop@ru.ac.za
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ABSTRACT

The use of antiretrovirals (ARVs) has drastically improved the life quality and expectancy of HIV patients since their introduction in health care. Several millions are still afflicted worldwide by HIV and ARV resistance is a constant concern for both healthcare practitioners and patients, as while treatment options are finite, the virus constantly adapts and selects for resistant viral strains under the pressure of drug treatment. The HIV protease is a crucial enzyme that processes viral polyproteins into their functional form, and has been a game changing drug target since the first application. Due to similarities in protease inhibitor designs, drug cross-resistance is not uncommon across ARVs of the same class. It is known that resistance against protease inhibitors is associated with a wider active site, but results from our large scale molecular dynamics analysis further show, for the first time, that there are regions of local expansions and compactions associated with high levels of resistance conserved across eight different protease inhibitors visible in their complexed form in closed receptor conformations. The method developed here is novel, supplementary to the methods of nonsynonymous mutation analysis, and should be applicable in analyzing the structural consequences of mutations in other contexts.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted July 30, 2018.
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Characterizing drug resistance using geometric ensembles from HIV protease dynamics
Olivier Sheik Amamuddy, Nigel T. Bishop, Özlem Tastan Bishop
bioRxiv 379958; doi: https://doi.org/10.1101/379958
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Characterizing drug resistance using geometric ensembles from HIV protease dynamics
Olivier Sheik Amamuddy, Nigel T. Bishop, Özlem Tastan Bishop
bioRxiv 379958; doi: https://doi.org/10.1101/379958

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