Assessing and improving the performance of consensus docking strategies using the DockBox package

Abstract

Molecular docking is a well‐established computational method to predict how a ligand binds to a specific protein target as well as to assess the strength of the binding. Although docking programs are used worldwide for drug discovery, it is not always simple to identify which program or combination of programs provides the best results for a target of interest. Here we present DockBox, a computational package designed to facilitate the use and comparison of multiple docking and scoring programs at a time, and to combine them using different consensus strategies. A new consensus docking method called scoring‐based consensus docking (SBCD) is introduced, which significantly improves success rates in pose prediction as well as virtual‐screening (VS) hit rates compared to standard consensus docking. Several test cases are presented to illustrate the success of the SBCD method in docking and VS scenarios. SBCD requires the same computational cost as standard consensus methods in terms of number of required programs, computational power and time, making it a promising new approach for the screening of large chemical libraries.Presentation of the DockBox packageFigure 1