Real-time ligand binding pocket database search using local surface descriptors

Abstract

Due to the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of a particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two dimensional pseudo-Zernike moments or the 3D Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark study employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed.

Computational Methods in Drug Discovery

“…Pocket matching. Methods like Catalytic Site Atlas (Porter et al, 2004), AFT (Arakaki et al, 2004), SURFACE (Ferre et al, 2004), POCKET-SURFER (Chikhi et al, 2010), and PATCH-SURFER (Sael and Kihara, 2012) detect similar pockets based on reference ligand binding sites. Catalytic Site Atlas contains annotated descriptors of enzyme active site residues as well as equivalent sites in related proteins found by sequence alignment.…”

Identification of Similar Binding Sites to Detect Distant Polypharmacology

“…3D-Zernike descriptors have also been shown suitable for local or global binding site description and comparisons. [113][114][115] As a final example, SiteAlign maps binding site properties on a faceted sphere located at its centre of mass. The alignment of such spheres is intended to provide a better tolerance of atomic variations and rotameric states than the rather crisp descriptions offered by pseudo-atom methods.…”

DARC: Mapping Surface Topography by Ray-Casting for Effective Virtual Screening at Protein Interaction Sites

“…These include methods based on Fourier correlation theory [89,90], spherical harmonics [91,92], geometric hashing [93], and negative images [94–96]. Most recently, others have used variations of ray-casting to compare internal pockets in proteins to one another [97,98]. In addition to their intended usage, a subtle – but very important – difference between the latter work and DARC is the origin from which rays emanate.…”