Docking analysis and resistance evaluation of clinically relevant mutations associated with the HIV-1 non-nucleoside reverse transcriptase inhibitors nevirapine, efavirenz and etravirine

Abstract

An integrated computational and statistical approach was used to determine the association of non-nucleoside reverse transcriptase inhibitors (NNRTIs) nevirapine, efavirenz and etravirine with resistance mutations that cause therapeutic failure and their impact on NNRTI resistance. Mutations detected for nevirapine virological failure with a prevalence greater than 10% in the used patient set were: K103N, Y181C, G190A, and K101E. A support vector regression model, based on matched genotypic/phenotypic data (n=850), showed that among 6365 analyzed mutations, K103N, Y181C and G190A have the first, third, and sixth greatest significance for nevirapine resistance, respectively. The most common indicator of treatment failure for efavirenz was K103N mutation present in 56.7% of the patients where the drug failed, followed by V108I, L100I, and G190A. For efavirenz resistance, K103N, G190, and L100I have the first, fourth, and eighth greatest significance, respectively, as determined in support vector regression model. No positive interactions were observed among nevirapine resistance mutations, while a more complex situation was observed with treatment failure of efavirenz and etravirine, characterized by the accumulation of multiple mutations. Docking simulations and free energy analysis based on docking scores of mutated human immunodeficiency virus (HIV) RT complexes were used to evaluate the influence of selected mutations on drug recognition. Results from support vector regression were confirmed by docking analysis. In particular, for nevirapine and efavirenz, a single mutation K103N was associated with the most unfavorable energetic profile compared to the wild-type sequence. This is in line with recent clinical data reporting that diarylpyrimidine etravirine, a very potent third generation drug effective against a wide range of drug-resistant HIV-1 variants, shows increased affinity towards K103N/S mutants due to its high conformational flexibility.