Combining docking, molecular dynamics and the linear interaction energy method to predict binding modes and affinities for non-nucleoside inhibitors to HIV-1 reverse transcriptase

Abstract

Docking, scoring, molecular dynamics (MD), and the linear interaction energy (LIE) method are used here to predict binding modes and affinities for a set of 43 non-nucleoside inhibitors to HIV-1 reverse transcriptase. Starting from a crystallographic structure, the binding modes of 43 inhibitors are predicted using automated docking. The Goldscore scoring function and the LIE method are then used to determine the relative binding free energies for the inhibitors. The Goldscore scoring function does not reproduce the relative binding affinities for the inhibitors, while the standard parametrization of the LIE method reproduces the experimental binding free energies for 39 inhibitors with an R (2) = 0.70 and an unsigned average error of 0.8 kcal/mol. The present calculations provide a validation of the combination of docking, MD, and LIE as a powerful tool in structure-based drug design, and the methodology is easily scalable for attaining a higher throughput of compounds.