The HIV-1 gag and protease: exploring the coevolving nature and structural implications of complex drug resistance mutational patterns in subtype C.

Abstract

Due to the high prevalence of HIV-1 subtype C infection coupled with increasing antiretroviral (ARV) drug treatment failure, the elucidation of complex resistance mutational patterns arsing through protein coevolution is required. Despite the inclusion of LPV and DRV in second- and third-line, many patients still fail treatment. In this study, protease (PR) inhibitor resistance mutations were identified by comparing treatment versus naïve sequences datasets in Gag and PR. Thereafter, to investigate Gag-PR coevolution and pathways to LPV resistance, phylogenetic analyses and Bayesian networks were constructed. Following this, structural analyses combining homology modelling, molecular docking and molecular dynamic simulations were carried out on specific patterns of protease resistance mutations (PRMs). To complement these analyses, the structural impact of a mutated Gag cleavage site on PR resistance dynamics was also evaluated. Accordingly, this study identified 12 major PRMs and several resistance combinations. Of these, the M46I+I54V+V82A pattern frequently occurred. The second most frequently recurring pattern included L76V as a fourth mutation to the above triplet. Coevolution analyses revealed correlations between positions 10, 46, 54 and 82 in PR. Of these, minor PRM L10F occurred in 6.4% of the dataset and was involved in pathways to LPV resistance. Additionally, Gag cleavage site (CS) mutation A431V was also correlated with L10F and the major PRMs. Distinct changes in PR’s active site, flap and elbow regions due to the PRMs (L10F, M46I, I54V, L76V, V82A) were found to alter LPV and DRV drug binding. When the PRMs were combined with the mutant Gag CS binding was greatly exacerbated. While the A431V Gag CS mutation coordinated several amino acid residues in PR, the L76V mutation was found to have a significant role in substrate recognition rather than directly inhibiting the drugs. These data show that the co-selection of mutations in Gag-PR greatly contributes to resistance outcomes and that our understanding on drug resistance is largely lacking, particularly where structure is concerned.