Abstract

BackgroundHIV-1 can develop resistance to antiretroviral drugs, mainly through mutations within the target regions of the drugs. In HIV-1 protease, a majority of resistance-associated mutations that develop in response to therapy with protease inhibitors are found in the protease’s active site that serves also as a binding pocket for the protease inhibitors, thus directly impacting the protease-inhibitor interactions. Some resistance-associated mutations, however, are found in more distant regions, and the exact mechanisms how these mutations affect protease-inhibitor interactions are unclear. Furthermore, some of these mutations, e.g. N88S and L76V, do not only induce resistance to the currently administered drugs, but contrarily induce sensitivity towards other drugs. In this study, mutations N88S and L76V, along with three other resistance-associated mutations, M46I, I50L, and I84V, are analysed by means of molecular dynamics simulations to investigate their role in complexes of the protease with different inhibitors and in different background sequence contexts.ResultsUsing these simulations for alchemical calculations to estimate the effects of mutations M46I, I50L, I84V, N88S, and L76V on binding free energies shows they are in general in line with the mutations’ effect on IC_{50} values. For the primary mutation L76V, however, the presence of a background mutation M46I in our analysis influences whether the unfavourable effect of L76V on inhibitor binding is sufficient to outweigh the accompanying reduction in catalytic activity of the protease. Finally, we show that L76V and N88S changes the hydrogen bond stability of these residues with residues D30/K45 and D30/T31/T74, respectively.ConclusionsWe demonstrate that estimating the effect of both binding pocket and distant mutations on inhibitor binding free energy using alchemical calculations can reproduce their effect on the experimentally measured IC_{50} values. We show that distant site mutations L76V and N88S affect the hydrogen bond network in the protease’s active site, which offers an explanation for the indirect effect of these mutations on inhibitor binding. This work thus provides valuable insights on interplay between primary and background mutations and mechanisms how they affect inhibitor binding.

Highlights

  • human immunodeficiency virus type 1 (HIV-1) can develop resistance to antiretroviral drugs, mainly through mutations within the target regions of the drugs

  • Estimation of resistance factors from the change in the inhibitor binding free energy We aimed to assess whether we can reproduce the ratios of experimentally measured resistance factors ( RFR = RFmutant /RFwildtype ) between the wildtype and mutant proteins by estimating the change in free energy of inhibitor binding upon mutations in the protease using molecular dynamics (MD) simulation with alchemical methods [37]

  • These complexes could be paired amongst each other such that the RF has been measured for the same inhibitor and the same protease strain with and without the mutation, namely: IDV and FPV with mutation M46I; IDV and FPV with mutation I50L; FPV, IDV, LPV, and SQV with mutation I84V; FPV and IDV with mutation N88S

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Summary

Introduction

HIV-1 can develop resistance to antiretroviral drugs, mainly through mutations within the target regions of the drugs. Some resistance-associated mutations, are found in more distant regions, and the exact mechanisms how these mutations affect protease-inhibitor interactions are unclear. Bastys et al Retrovirology (2020) 17:13 individuals receive antiretroviral therapy (ART) [2], acquired immune deficiency syndrome (AIDS)-related deaths have dropped to 1 million per year [1] For those under treatment, resistance towards drugs is a major cause for the need for switching of the therapy. Several RAMs are found in distant to the binding pocket sites, e.g. in the amino acids N88 and L90 in the protease’s α-helix or L76 in the protein’s hydrophobic core The effect of these mutations on inhibitor binding is likely to be not through direct interactions with PIs. RF polymorphisms IDV SQV LPV FPV.

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