Most computational models of protein-ligand interactions consider only the energetics of the final bound state of the complex and do not examine the dynamics of the ligand as it enters the binding site. We have developed a novel approach to studying the dynamics of protein-ligand interactions based on motion planning algorithms from the field of robotics. We model the flexible ligand as an `articulated robot' where each link of the robot corresponds to an atomic bond with one torsional degree of freedom. Our algorithm uses electrostatic and van der Waals potentials to compute the most energetically favorable path between any given initial and goal ligand configurations. We use a probabilistic motion planning approach to sample the distribution of possible paths to a given goal configuration and compute an energy based "difficulty weight" for each path. By statistically averaging this weight over several randomly generated starting configurations, we compute the relative difficulty of e...
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