title: AlphaSpace: Fragment-Centric Topographical Mapping To Target Protein-Protein Interaction Interfaces.
abstract: Inhibition of protein-protein interactions (PPIs) is emerging as a promising therapeutic strategy despite the difficulty in targeting such interfaces with drug-like small molecules. PPIs generally feature large and flat binding surfaces as compared to typical drug targets. These features pose a challenge for structural characterization of the surface using geometry-based pocket-detection methods. An attractive mapping strategy--that builds on the principles of fragment-based drug discovery (FBDD)--is to detect the fragment-centric modularity at the protein surface and then characterize the large PPI interface as a set of localized, fragment-targetable interaction regions. Here, we introduce AlphaSpace, a computational analysis tool designed for fragment-centric topographical mapping (FCTM) of PPI interfaces. Our approach uses the alpha sphere construct, a geometric feature of a protein's Voronoi diagram, to map out concave interaction space at the protein surface. We introduce two new features--alpha-atom and alpha-space--and the concept of the alpha-atom/alpha-space pair to rank pockets for fragment-targetability and to facilitate the evaluation of pocket/fragment complementarity. The resulting high-resolution interfacial map of targetable pocket space can be used to guide the rational design and optimization of small molecule or biomimetic PPI inhibitors.
authors.affiliation: Department of Chemistry, New York University , New York, New York 10003, United States.
authors.forename: David
authors.initials: D
authors.lastname: Rooklin
authors.affiliation: Department of Chemistry, New York University , New York, New York 10003, United States.
authors.forename: Cheng
authors.initials: C
authors.lastname: Wang
authors.affiliation: Department of Chemistry, New York University , New York, New York 10003, United States.
authors.forename: Joseph
authors.initials: J
authors.lastname: Katigbak
authors.affiliation: Department of Chemistry, New York University , New York, New York 10003, United States.
authors.forename: Paramjit S
authors.initials: PS
authors.lastname: Arora
authors.affiliation: Department of Chemistry, New York University , New York, New York 10003, United States.|NYU-ECNU Center for Computational Chemistry at NYU Shanghai , Shanghai 200062, China.
authors.forename: Yingkai
authors.initials: Y
authors.lastname: Zhang
mesh_terms: D001665:Binding Sites / Q000187:drug effects; D030562:Databases, Protein; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D008024:Ligands; D008958:Models, Molecular; D058990:Molecular Targeted Therapy; D011485:Protein Binding; D054730:Protein Interaction Domains and Motifs / Q000187:drug effects; D025941:Protein Interaction Mapping / Q000379:methods*; D060066:Protein Interaction Maps / Q000187:drug effects*; D011506:Proteins / Q000737:chemistry / Q000378:metabolism*; D051736:Proto-Oncogene Proteins c-mdm2 / Q000737:chemistry / Q000378:metabolism; D016159:Tumor Suppressor Protein p53 / Q000737:chemistry / Q000378:metabolism
chemical_list: D008024:Ligands; D011506:Proteins; D016159:Tumor Suppressor Protein p53; D051736:Proto-Oncogene Proteins c-mdm2