Structure‐based phenotyping predicts HIV‐1 protease inhibitor resistance

Mutations in HIV‐1 drug targets lead to resistance and consequent therapeutic failure of antiretroviral drugs. Phenotypic resistance assays are time‐consuming and costly, and genotypic rules‐based interpretations may fail to predict the effects of multiple mutations. We have developed a computational procedure that rapidly evaluates changes in the binding energy of inhibitors to mutant HIV‐1 PR variants. Models of WT complexes were produced from crystal structures. Mutant complexes were built by amino acid substitutions in the WT complexes with subsequent energy minimization of the ligand and PR binding site residues. Accuracy of the models was confirmed by comparison with available crystal structures and by prediction of known resistance‐related mutations. PR variants from clinical isolates were modeled in complex with six FDA‐approved PIs, and changes in the binding energy (ΔE_bind) of mutant versus WT complexes were correlated with the ratios of phenotypic 50% inhibitory concentration (IC₅₀) values. The calculated ΔE_bind of five PIs showed significant correlations (R² = 0.7–0.8) with IC₅₀ ratios from the Virco Antivirogram assay, and the ΔE_bind of six PIs showed good correlation (R² = 0.76–0.85) with IC₅₀ ratios from the Virologic PhenoSense assay. ΔE_bind cutoffs corresponding to a four‐fold increase in IC₅₀ were used to define the structure‐based phenotype as susceptible, resistant, or equivocal. Blind predictions for 78 PR variants gave overall agreement of 92% (kappa = 0.756) and 86% (kappa = 0.666) with PhenoSense and Antivirogram phenotypes, respectively. The structural phenotyping predicted drug resistance of clinical HIV‐1 PR variants with an accuracy approaching that of frequently used cell‐based phenotypic assays.