title: Self-organizing fuzzy graphs for structure-based comparison of protein pockets.
abstract: Patterns of receptor-ligand interaction can be conserved in functionally equivalent proteins even in the absence of sequence homology. Therefore, structural comparison of ligand-binding pockets and their pharmacophoric features allow for the characterization of so-called "orphan" proteins with known three-dimensional structure but unknown function, and predict ligand promiscuity of binding pockets. We present an algorithm for rapid pocket comparison (PoLiMorph), in which protein pockets are represented by self-organizing graphs that fill the volume of the cavity. Vertices in these three-dimensional frameworks contain information about the local ligand-receptor interaction potential coded by fuzzy property labels. For framework matching, we developed a fast heuristic based on the maximum dispersion problem, as an alternative to techniques utilizing clique detection or geometric hashing algorithms. A sophisticated scoring function was applied that incorporates knowledge about property distributions and ligand-receptor interaction patterns. In an all-against-all virtual screening experiment with 207 pocket frameworks extracted from a subset of PDBbind, PoLiMorph correctly assigned 81% of 69 distinct structural classes and demonstrated sustained ability to group pockets accommodating the same ligand chemotype. We determined a score threshold that indicates "true" pocket similarity with high reliability, which not only supports structure-based drug design but also allows for sequence-independent studies of the proteome.
authors.affiliation: Computer-Assisted Drug Design, Eidgenössische Technische Hochschule, Zürich, Zürich, Switzerland.
authors.forename: Felix
authors.initials: F
authors.lastname: Reisen
authors.forename: Martin
authors.initials: M
authors.lastname: Weisel
authors.forename: Jan M
authors.initials: JM
authors.lastname: Kriegl
authors.forename: Gisbert
authors.initials: G
authors.lastname: Schneider
mesh_terms: D000465:Algorithms; D000818:Animals; D001665:Binding Sites; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D006801:Humans; D008024:Ligands; D008958:Models, Molecular; D011485:Protein Binding; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry* / Q000145:classification / Q000378:metabolism; D013329:Structure-Activity Relationship
chemical_list: D008024:Ligands; D011506:Proteins