Optimizing Low Energy Pathways in Receptor-Ligand Binding with Motion Planning

Determination of ligand binding pathways is an important factor to predict drug efficacy in drug discovery. Ligand-receptor binding involves the motion of many degrees of freedom, which can make binding pathways difficult to discover with traditional methods. Interactive molecular docking tools can allow users to explore the high dimensional energy landscape of the ligand-receptor system with rigid molecular models to determine low energy ligand states and pathways to binding. To introduce the effect of ligand flexibility in molecular docking with rigid body models, we use ensembles of distinct ligand conformation states that can be swapped during exploration. Our method emulates ligand flexibility effects in rigid body docking at no extra computational cost. Our automated method simulates user search performance with a path optimization algorithm. We find that allowing the algorithm to include different ligand conformations in its search for states of lower energy can result in optimized low energy pathways with reduced search times in difficult areas near energy barriers. This method can be adapted to include molecular flexibility effects in interactive rigid body molecular docking running in commodity hardware, such as molecular docking games.