Statistical Profiling of One Promiscuous Protein Binding Site: Illustrated by Urokinase Catalytic Domain. Issue 10 (11th July 2017)

• Record Type: Journal Article
• Authors: Cerisier, Natacha; Regad, Leslie; Triki, Dhoha; Petitjean, Michel; Flatters, Delphine; Camproux, Anne‐Claude
• Is Part Of: Molecular informatics. Volume 36:Issue 10(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-07-11
• Subjects: Urokinases -- proteochemometric modeling -- statistical profiling -- binding site -- protein-ligand recognition; Cheminformatics -- Periodicals; QSAR (Biochemistry) -- Periodicals; Structure-activity relationships (Biochemistry) -- Periodicals; Drugs -- Structure-activity relationships -- Periodicals; 615.19
• DOI: 10.1002/minf.201700040
• Languages: English
• ISSNs: 1868-1743

Abstract

Abstract: While recent literature focuses on drug promiscuity, the characterization of promiscuous binding sites (ability to bind several ligands) remains to be explored. Here, we present a proteochemometric modeling approach to analyze diverse ligands and corresponding multiple binding sub‐pockets associated with one promiscuous binding site to characterize protein‐ligand recognition. We analyze both geometrical and physicochemical profile correspondences. This approach was applied to examine the well‐studied druggable urokinase catalytic domain inhibitor binding site, which results in a large number of complex structures bound to various ligands. This approach emphasizes the importance of jointly characterizing pocket and ligand spaces to explore the impact of ligand diversity on sub‐pocket properties and to establish their main profile correspondences. This work supports an interest in mining available 3D holo structures associated with a promiscuous binding site to explore its main protein‐ligand recognition tendency. Abstract :