Amit P. Singh, Jean-Claude Latombe, Douglas L. Brutlag
Abstract
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 technique for studying the dynamics of protein-ligand
interactions based on motion planning algorithms from the field
of robotics. 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 probabilistic
motion planning 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 entering and leaving a given binding
configuration. This approach yields details of the energy contours
around the binding site and can be used to characterize and predict
good binding sites. Results from tests with three protein-ligand
complexes indicate that our algorithm is able to detect energy
barriers around the true binding site that distinguish this site
from other predicted low-energy binding sites.