Title

Elucidating the Interdependence of Drug Resistance from Combinations of Mutations

UMMS Affiliation

Department of Biochemistry and Molecular Pharmacology; Department of Medicine; Program in Bioinformatics and Integrative Biology; Schiffer Lab

Publication Date

9-15-2017

Document Type

Article

Disciplines

Biochemistry | Medicinal Chemistry and Pharmaceutics | Medicinal-Pharmaceutical Chemistry | Molecular Biology | Structural Biology

Abstract

HIV-1 protease is responsible for the cleavage of 12 nonhomologous sites within the Gag and Gag-Pro-Pol polyproteins in the viral genome. Under the selective pressure of protease inhibition, the virus evolves mutations within (primary) and outside of (secondary) the active site, allowing the protease to process substrates while simultaneously countering inhibition. The primary protease mutations impede inhibitor binding directly, while the secondary mutations are considered accessory mutations that compensate for a loss in fitness. However, the role of secondary mutations in conferring drug resistance remains a largely unresolved topic. We have shown previously that mutations distal to the active site are able to perturb binding of darunavir (DRV) via the protein's internal hydrogen-bonding network. In this study, we show that mutations distal to the active site, regardless of context, can play an interdependent role in drug resistance. Applying eigenvalue decomposition to collections of hydrogen bonding and van der Waals interactions from a series of molecular dynamics simulations of 15 diverse HIV-1 protease variants, we identify sites in the protease where amino acid substitutions lead to perturbations in nonbonded interactions with DRV and/or the hydrogen-bonding network of the protease itself. While primary mutations are known to drive resistance in HIV-1 protease, these findings delineate the significant contributions of accessory mutations to resistance. Identifying the variable positions in the protease that have the greatest impact on drug resistance may aid in future structure-based design of inhibitors.

DOI of Published Version

10.1021/acs.jctc.7b00601

Source

J Chem Theory Comput. 2017 Nov 14;13(11):5671-5682. doi: 10.1021/acs.jctc.7b00601. Epub 2017 Oct 9. Link to article on publisher's site

Journal/Book/Conference Title

Journal of chemical theory and computation

Related Resources

Link to Article in PubMed

PubMed ID

28915040

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