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dc.creatorFlynn, WF
dc.creatorHaldane, A
dc.creatorTorbett, BE
dc.creatorLevy, RM
dc.date.accessioned2021-01-25T21:02:00Z
dc.date.available2021-01-25T21:02:00Z
dc.date.issued2017-01-01
dc.identifier.issn0737-4038
dc.identifier.issn1537-1719
dc.identifier.doihttp://dx.doi.org/10.34944/dspace/4958
dc.identifier.other28369521 (pubmed)
dc.identifier.urihttp://hdl.handle.net/20.500.12613/4976
dc.description.abstract© The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. Understanding the complex mutation patterns that give rise to drug resistant viral strains provides a foundation for developing more effective treatment strategies for HIV/AIDS. Multiple sequence alignments of drug-experienced HIV-1 protease sequences contain networks of many pair correlations which can be used to build a (Potts) Hamiltonian model of these mutation patterns. Using this Hamiltonian model, we translate HIV-1 protease sequence covariation data into quantitative predictions for the probability of observing specific mutation patterns which are in agreement with the observed sequence statistics. We find that the statistical energies of the Potts model are correlated with the fitness of individual proteins containing therapy-associated mutations as estimated by in vitro measurements of protein stability and viral infectivity. We show that the penalty for acquiring primary resistance mutations depends on the epistatic interactions with the sequence background. Primary mutations which lead to drug resistance can become highly advantageous (or entrenched) by the complex mutation patterns which arise in response to drug therapy despite being destabilizing in the wildtype background. Anticipating epistatic effects is important for the design of future protease inhibitor therapies.
dc.format.extent1291-1306
dc.language.isoen
dc.relation.haspartMolecular Biology and Evolution
dc.relation.isreferencedbyOxford University Press (OUP)
dc.rightsCC BY
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectepistasis
dc.subjectmutational landscape
dc.subjectstatistical inference
dc.subjectcoevolution
dc.subjectHIV
dc.subjectdrug resistance
dc.titleInference of epistatic effects leading to entrenchment and drug resistance in HIV-1 protease
dc.typeArticle
dc.type.genreJournal Article
dc.relation.doi10.1093/molbev/msx095
dc.ada.noteFor Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.edu
dc.date.updated2021-01-25T21:01:56Z
refterms.dateFOA2021-01-25T21:02:00Z


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