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Unsupervised guided docking of covalently bound ligands
Authors:Xavier?Fradera  author-information"  >  author-information__contact u-icon-before"  >  mailto:X.Fradera@organon.co.uk"   title="  X.Fradera@organon.co.uk"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author,Jasmit?Kaur,Jordi?Mestres
Affiliation:(1) Department of Medicinal Chemistry, Organon Laboratories Ltd., Newhouse, Lanarkshire, ML1 5SH Scotland, UK;(2) Present address: OSI Pharmaceuticals, Watlington Road, Oxford, OX46LT, UK;(3) Present address: Institut Municipal d"lsquo"Investigació Mèdica, Universitat Pompeu Fabra, Passeig Marítim de la Barceloneta, 37–49, Barcelona, Spain
Abstract:Summary An approach for docking covalently bound ligands in protein enzymes or receptors was implemented in MacDOCK, a similarity-driven docking program based on DOCK 4.0. This approach was tested with a small number of covalent ligand–protein structures, using both native and non-native protein structures. In all cases, MacDOCK was able to generate orientations consistent with the known covalent binding mode of these complexes, with a performance similar to that of other docking programs. This method was also applied to search for known covalent thrombin inhibitors in a medium-sized molecular database (ca. 11,000 compounds). Detection of functional groups suitable for covalent docking was carried out automatically. A significant enrichment in known active molecules in the first 5% of the database was obtained, showing that MacDOCK can be used efficiently for the virtual screening of covalently bound ligands.
Keywords:covalently bound ligands  molecular similarity  protein–  ligand docking  thrombin  virtual screening
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