moleculeGL: A Recursive, Metropolis Monte Carlo Rotamer-Design Algorithm

Peter Kekenes-Huskey, California Institute of Technology

A wealth of computational strategies is available for predicting the binding site and affinities of a putative ligand inside a target receptor. Although numerous techniques have been reported for the orientation of ligands or fragments thereof, few methods have delved into improving the accuracy of generating reliable ligand conformations within predicted binding modes. In an effort to comprehensively sample the torsion space available to a flexible ligand and focus on low energy conformations, a recursive, Metropolis Monte Carlo-based rotamer design technique, moleculeGL, has been developed. moleculeGL recursively samples adjacent rotatable bonds from a defined anchor and directs the search along low energy pathways, such that high-affinity conformations of the ligand can be identified. Furthermore, this program applies spatial constraints within the search that restrict the solutions to structurally dissimilar conformations, thus encouraging diversity in the solution set. The performance of moleculeGL has been evaluated for a set of 50 cocrystals, with the number of rotatable bonds for the ligands varying from 2 to 8. About 82% of the structures were predicted within 2.0 Å root mean squared deviation (RMSD) of the crystal structure, starting from an arbitrary ligand conformation. This high level of accuracy suggests moleculeGL’s applicability to the design of pharmacaphore substituents, for which the position of a chemically-active pharmacaphore is well-known.

Abstract Author(s): Kekenes-Huskey, Peter M., Nagarajan Vaidehi, William A. Goddard, III