Prediction of Binding Affinities for TIBO Inhibitors of HIV-1 Reverse Transcriptase Using Monte Carlo Simulations in a Linear Response Method

Monte Carlo (MC) simulations in combination with a linear response approach were used to estimate the free energies of binding for a series of 12 TIBO nonnucleoside inhibitors of HIV-1 reverse transcriptase. Separate correlations were made for the R 6 and S 6 absolute conformations of the inhibitors, as well as for the analogous N6-monoprotonated species. Models based upon the neutral unbound inhibitors produced overall better fits to experimental values than did those using the protonated unbound inhibitors, with only slight differences between the neutral R 6 and S 6 cases. The best results were obtained with a three-parameter linear response equation containing van der Waals (α), electrostatic (β), and solvent accessible surface area (SASA, γ) terms. The averaged (R 6 and S 6) rms error was approximately 0.88 kcal/mol for the observed range of 4.06 kcal/mol in inhibitor activities. The averaged values of α, β, and γ were −0.150, 0.114, and 0.0286, respectively. Omission of the α term gave β 0.152 and γ 0.022 with a rms of 0.92. The unweighted van der Waals components were found to be highly attractive but failed to correlate well across the series of inhibitors. Contrastingly, while the electrostatic components are all repulsive, they show a direct correlation with inhibitor activity as measured by ΔG binding. The role of γ is primarily to produce an overall negative binding energy, and it can effectively be replaced with a negative constant. During the MC simulations of the unbound solvated inhibitors, the R 6 and S 6 absolute conformations do not interconvert due to the formation of a favorable hydrogen bond to solvent. In the complex, however, interconversion of these conformations of the inhibitor is observed during the course of the simulations, a phenomenon which is apparently not observed in the crystalline state of the complex. Hydrogen bonding of the inhibitor to the backbone NH of K101 and the lack of such an interaction with the CO of K101 or with solvent correlate with enhanced activity, as does the ability to assume a number of different orientations of the inhibitor dimethylallyl moiety with respect to residues Y181 and Y188 while retaining contact with W229. Overall, the use of a combination of MC simulation with a linear response method shows promise as a relatively rapid means of estimating inhibitor activities. This approach should be useful in the preliminary evaluation of potential modifications to known inhibitors to enhance activi