Hot-Spots-Guided Receptor-Based Pharmacophores (HS-Pharm): A Knowledge-Based Approach to Identify Ligand-Anchoring Atoms in Protein Cavities and Prioritize Structure-Based Pharmacophores Export

@article{citeulike:3006352, abstract = {PMID: 18570371 The design of biologically active compounds from ligand-free protein structures using a structure-based approach is still a major challenge. In this paper, we present a fast knowledge-based approach (HS-Pharm) that allows the prioritization of cavity atoms that should be targeted for ligand binding, by training machine learning algorithms with atom-based fingerprints of known ligand-binding pockets. The knowledge of hot spots for ligand binding is here used for focusing structure-based pharmacophore models. Three targets of pharmacological interest (neuraminidase, β2 adrenergic receptor, and cyclooxygenase-2) were used to test the evaluated methodology, and the derived structure-based pharmacophores were used in retrospective virtual screening studies. The current study shows that structure-based pharmacophore screening is a powerful technique for the fast identification of potential hits in a chemical library, and that it is a valid alternative to virtual screening by molecular docking.}, address = {Bioinformatics of the Drug, UMR 7175 CNRS-ULP (Université Louis Pasteur-Strasbourg I), 74 route du Rhin, B.P. 24, F-67400 Illkirch, France, and Laboratoire d'Infochimie, UMR 7551 CNRS, Université Louis Pasteur-Strasbourg I, 4 rue B. Pascal, F-67000 Strasbourg, France didier.rognan@pharma.u-strasbg.fr.}, author = {Barillari, Caterina and Marcou, Gilles and Rognan, Didier}, citeulike-article-id = {3006352}, citeulike-linkout-0 = {http://dx.doi.org/10.1021/ci800064z}, citeulike-linkout-1 = {http://pubs.acs.org/doi/abs/10.1021/ci800064z}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/18570371}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=18570371}, day = {1}, doi = {10.1021/ci800064z}, issn = {1549-9596}, journal = {Journal of Chemical Information and Modeling}, keywords = {agonist, b2ar, binding, docking, drug, ligands, pharmacology, theory}, month = {July}, number = {7}, pages = {1396--1410}, posted-at = {2009-10-05 18:45:05}, priority = {2}, title = {Hot-Spots-Guided Receptor-Based Pharmacophores (HS-Pharm): A Knowledge-Based Approach to Identify Ligand-Anchoring Atoms in Protein Cavities and Prioritize Structure-Based Pharmacophores}, url = {http://dx.doi.org/10.1021/ci800064z}, volume = {48}, year = {2008} }

TY - JOUR ID - citeulike:3006352 L3 - citeulike-article-id:3006352 N2 - PMID: 18570371 The design of biologically active compounds from ligand-free protein structures using a structure-based approach is still a major challenge. In this paper, we present a fast knowledge-based approach (HS-Pharm) that allows the prioritization of cavity atoms that should be targeted for ligand binding, by training machine learning algorithms with atom-based fingerprints of known ligand-binding pockets. The knowledge of hot spots for ligand binding is here used for focusing structure-based pharmacophore models. Three targets of pharmacological interest (neuraminidase, β2 adrenergic receptor, and cyclooxygenase-2) were used to test the evaluated methodology, and the derived structure-based pharmacophores were used in retrospective virtual screening studies. The current study shows that structure-based pharmacophore screening is a powerful technique for the fast identification of potential hits in a chemical library, and that it is a valid alternative to virtual screening by molecular docking. IS - 7 JF - Journal of Chemical Information and Modeling SN - 1549-9596 AD - Bioinformatics of the Drug, UMR 7175 CNRS-ULP (Université Louis Pasteur-Strasbourg I), 74 route du Rhin, B.P. 24, F-67400 Illkirch, France, and Laboratoire d’Infochimie, UMR 7551 CNRS, Université Louis Pasteur-Strasbourg I, 4 rue B. Pascal, F-67000 Strasbourg, France didier.rognan@pharma.u-strasbg.fr. EP - 1410 TI - Hot-Spots-Guided Receptor-Based Pharmacophores (HS-Pharm): A Knowledge-Based Approach to Identify Ligand-Anchoring Atoms in Protein Cavities and Prioritize Structure-Based Pharmacophores VL - 48 SP - 1396 KW - agonist KW - b2ar KW - binding KW - docking KW - drug KW - ligands KW - pharmacology KW - theory AU - Barillari, Caterina AU - Marcou, Gilles AU - Rognan, Didier PY - 2008/07/01/ UR - http://dx.doi.org/10.1021/ci800064z ER -