Activity predictions for efavirenz analogues with the K103N mutant of HIV reverse transcriptase.

Monte Carlo-extended linear response (MC/ELR) calculations are used to examine the binding of efavirenz analogues with the K103N mutant of HIV-1 reverse transcriptase (HIVRT). A regression equation previously reported for the wild type (WT) enzyme is shown to predict 47 experimental activities for the K103N mutant with a q(2)=0.55 and avg error of only 0.

Prediction of activity for nonnucleoside inhibitors with HIV-1 reverse transcriptase based on Monte Carlo simulations.

Results of Monte Carlo (MC) simulations for more than 200 nonnucleoside inhibitors of HIV-1 reverse transcriptase (NNRTIs) representing eight diverse chemotypes have been correlated with their anti-HIV activities in an effort to establish simulation protocols and methods that can be used in the development of more effective drugs. Each inhibitor was modeled in a complex with the protein and by itself in water, and potentially useful descriptors of binding affinity were collected during the MC simulations. A viable regression equation was obtained for each data set using an extended linear response approach, which yielded r(2) values between 0.