Drug resistance continues to be a growing global problem. The efficacy of small molecule inhibitors is threatened by pools of genetic diversity in all systems, including antibacterials, antifungals, cancer therapeutics, and antivirals. Resistant variants often include combinations of active site mutations and distal "secondary" mutations, which are thought to compensate for losses in enzymatic activity. HIV-1 protease is the ideal model system to investigate these combinations and underlying molecular mechanisms of resistance. Darunavir (DRV) binds wild-type (WT) HIV-1 protease with a potency of <5 pM, but we have identified a protease variant that loses potency to DRV 150 000-fold, with 11 mutations in and outside the active site. To elucidate the roles of these mutations in DRV resistance, we used a multidisciplinary approach, combining enzymatic assays, crystallography, and molecular dynamics simulations. Analysis of protease variants with 1, 2, 4, 8, 9, 10, and 11 mutations showed that the primary active site mutations caused ∼50-fold loss in potency (2 mutations), while distal mutations outside the active site further decreased DRV potency from 13 nM (8 mutations) to 0.76 μM (11 mutations). Crystal structures and simulations revealed that distal mutations induce subtle changes that are dynamically propagated through the protease. Our results reveal that changes remote from the active site directly and dramatically impact the potency of the inhibitor. Moreover, we find interdependent effects of mutations in conferring high levels of resistance. These mechanisms of resistance are likely applicable to many other quickly evolving drug targets, and the insights may have implications for the design of more robust inhibitors.
HIV-1 protease is one of the prime targets of agents used in antiretroviral therapy against HIV. However, under selective pressure of protease inhibitors, primary mutations at the active site weaken inhibitor binding to confer resistance. Darunavir (DRV) is the most potent HIV-1 protease inhibitor in clinic; resistance is limited, as DRV fits well within the substrate envelope. Nevertheless, resistance is observed due to hydrophobic changes at residues including I50, V82 and I84 that line the S1/S1' pocket within the active site. Through enzyme inhibition assays and a series of 12 crystal structures, we interrogated susceptibility of DRV and two potent analogs to primary S1' mutations. The analogs had modifications at the hydrophobic P1' moiety compared to DRV to better occupy the unexploited space in the S1' pocket where the primary mutations were located. Considerable losses of potency were observed against protease variants with I84V and I50V mutations for all three inhibitors. The crystal structures revealed an unexpected conformational change in the flap region of I50V protease bound to the analog with the largest P1' moiety, indicating interdependency between the S1' subsite and the flap region. Collective analysis of protease-inhibitor interactions in the crystal structures using principle component analysis was able to distinguish inhibitor identity and relative potency solely based on vdW contacts. Our results reveal the complexity of the interplay between inhibitor P1' moiety and S1' mutations, and validate principle component analyses as a useful tool for distinguishing resistance and inhibitor potency.
The evolution of HIV-1 protein sequences should be governed by a combination of factors including nucleotide mutational probabilities, the genetic code, and fitness. The impact of these factors on protein sequence evolution is interdependent, making it challenging to infer the individual contribution of each factor from phylogenetic analyses alone. We investigated the protein sequence evolution of HIV-1 by determining an experimental fitness landscape of all individual amino acid changes in protease. We compared our experimental results to the frequency of protease variants in a publicly available data set of 32,163 sequenced isolates from drug-naïve individuals. The most common amino acids in sequenced isolates supported robust experimental fitness, indicating that the experimental fitness landscape captured key features of selection acting on protease during viral infections of hosts. Amino acid changes requiring multiple mutations from the likely ancestor were slightly less likely to support robust experimental fitness than single mutations, consistent with the genetic code favoring chemically conservative amino acid changes. Amino acids that were common in sequenced isolates were predominantly accessible by single mutations from the likely protease ancestor. Multiple mutations commonly observed in isolates were accessible by mutational walks with highly fit single mutation intermediates. Our results indicate that the prevalence of multiple-base mutations in HIV-1 protease is strongly influenced by mutational sampling.
Protease inhibitors have the highest potency among antiviral therapies against HIV-1 infections, yet the virus can evolve resistance. Darunavir (DRV), currently the most potent Food and Drug Administration-approved protease inhibitor, retains potency against single-site mutations. However, complex combinations of mutations can confer resistance to DRV. While the interdependence between mutations within HIV-1 protease is key for inhibitor potency, the molecular mechanisms that underlie this control remain largely unknown. In this study, we investigated the interdependence between the L89V and L90M mutations and their effects on DRV binding. These two mutations have been reported to be positively correlated with one another in HIV-1 patient-derived protease isolates, with the presence of one mutation making the probability of the occurrence of the second mutation more likely. The focus of our investigation is a patient-derived isolate, with 24 mutations that we call “KY”; this variant includes the L89V and L90M mutations. Three additional KY variants with back-mutations, KY(V89L), KY(M90L), and the KY(V89L/M90L) double mutation, were used to experimentally assess the individual and combined effects of these mutations on DRV inhibition and substrate processing. The enzymatic assays revealed that the KY(V89L) variant, with methionine at residue 90, is highly resistant, but its catalytic function is compromised. When a leucine to valine mutation at residue 89 is present simultaneously with the L90M mutation, a rescue of catalytic efficiency is observed. Molecular dynamics simulations of these DRV-bound protease variants reveal how the L90M mutation induces structural changes throughout the enzyme that undermine the binding interactions.
The author list for this paper should appear as it does in this Addition and Correction. Daniel N. A. Bolon was inadvertently left off the author listing and should be added. The gag processing experiment (results shown in Figure S1) was performed in his laboratories by Dr. Nachum.
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