Accurate detection of protein:ligand binding sites using molecular dynamics simulations

Accurate prediction of location of cavities and surface grooves in proteins is important, as these are potential sites for ligand binding. Several currently available programs for cavity detection are unable to detect cavities near the surface or surface grooves. In the present study, an optimized molecular dynamics based procedure is described for detection and quantification of interior cavities as well as surface pockets. This is based on the observation that the mobility of water in such pockets is significantly lower than that of bulk water. The algorithm efficiently detects surface grooves that are sites of protein-ligand and protein-protein interaction. The algorithm was also used to substantially improve the performance of an automated docking procedure for docking monomers of nonobligate protein-protein complexes. In addition, it was applied to predict key residues involved in the binding of the E. coli toxin CcdB with its inhibitor. Predictions were subsequently validated by mutagenesis experiments.