Accurate Detection of Protein:Ligand Binding Sites Using Molecular Dynamics Simulations

Abstract

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.

Catalytic residues in hydrolases: analysis of methods designed for ligand-binding site prediction

“…They exploit a wealth of knowledge included in a training set, and aim at predicting specific functional roles of residues rather than broadly defined ligand-binding sites. Apart from the methods devoted to prediction of functional sites, alternative approaches such as molecular dynamics simulations [58] or docking [59–61] were successfully employed to identify ligand-binding sites. A thorough review of strategies for ligand-binding site detection is presented elsewhere [62].…”

Looking at Enzymes from the Inside out: The Proximity of Catalytic Residues to the Molecular Centroid can be used for Detection of Active Sites and Enzyme–Ligand Interfaces

“…38,[40][41][42][43][44][45][46][47] Other methods exploit physical properties that stem from the tendency of active sites to be clefts, such as the distribution of electrostatic potential emanating from a uniform distribution of charges within the protein volume, 48 the propensity of organic molecules to accumulate in cavities 49 and the lower mobility of water molecules located in cavities. 50 Most geometry based prediction methods define protein envelopes 38,[40][41][42][43][44][45][46][47]51,52 (protein "sea level") in order to recognize and rank pockets and cavities. The different definitions of the envelope and the consequent different characterization of cavities affect the prediction performance of these methods.…”

Variation in structural location and amino acid conservation of functional sites in protein domain families

“…In contrast to structural approaches that search for ligand binding pockets on the protein surface using molecular modelling [4,5], network analysis [6], or compare the protein surface to structures with known interacting sites [7,8], many methods are based on a set of homologous sequences combined with evolutionary or structural information. The evolutionary trace (ET) method [9,10], for example, searches for a structural cluster of conserved residues.…”