A path planning approach for computing large-amplitude motions of flexible molecules

Motion is inherent in molecular interactions. Molecular flexibility must be taken into account in order to develop accurate computational techniques for predicting interactions. Energy-based methods currently used in molecular modeling (i.e. molecular dynamics, Monte Carlo algorithms) are, in practice, only able to compute local motions while accounting for molecular flexibility. However, large-amplitude motions often occur in biological processes. We investigate the application of geometric path planning algorithms to compute such large motions in flexible molecular models. Our purpose is to exploit the efficacy of a geometric conformational search as a filtering stage before subsequent energy refinements.

In this paper two kinds of large-amplitude motion are treated: protein loop conformational changes (involving protein backbone flexibility) and ligand trajectories to deep active sites in proteins (involving ligand and protein side-chain flexibility). First studies performed using our two-stage approach (geometric search followed by energy refinements) show that, compared to classical molecular modeling methods, quite similar results can be obtained with a performance gain of several orders of magnitude. Furthermore, our results also indicate that the geometric stage can provide highly valuable information to biologists.

The algorithms have been implemented in the general-purpose motion planning software Move3D, developed at LAAS-CNRS. We are currently working on an optimized stand-alone library that will be available to the scientific community.