Validation of Model of Cytochrome P450 2D6 An in Silico Tool for 对细胞色素P450 2D6在硅片工具，模型验证.ppt

Validation of Model of Cytochrome P450 2D6: An in Silico Tool for PredictingMetabolism and Inhibition Carol A. Kemp, Jack U. Flanagan, Annamaria J. van Eldik, Jean-Didier Mare′chal, C. Roland Wolf, Gordon C. K. Roberts,§ Mark J. I. Paine Michael J. Sutcliffe J. Med. Chem. 2004 Cytochrome P450 (Cyp450) Group of oxidative enzymes Exits in all lineages Membrane protein (ER, mitochondria) Metabolite thousands of endogenous and exogenous compounds Importance of Cyp 2D6 Oxidation of 50 drugs Inhibited by drugs Research Goals Previous work: HM + docking position metabolism site above heme Typical (basic nitrogen) substrates Screening a database for CYP2D6 inhibitors Can 3D method improve over 2D approach Asses model accuracy Comparative Modeling of 2D6 FSSP = Fold classification Secondary Structure Alignment (DALI) Model Validation Screened Available Databases Ekins ( 21 compounds ) Creating an Additional Dataset NCI database (compounds tested for treating cancer) Weight ~ Ekins Strobl datasets 4 Ring Systems Availability 33 Compunds Consistency with known inhibition measurements Predicting inhibition using Docking Questions for discussion Is the method applicable for large scale database scanning ? (~7 min CPU on a one processor Silicon Graphics R14) Can substrate affinity be predicted with the same accuracy ? Are positions reliable enough for predicting drug-drug interactions ? Thank you for your attention * Cytochrome P450 2D6 Analgesics (pain killers) Beta Blockers (cardiovascular diseases) Quinidine (heart rhythm disturbance) fluoxertine (depression) Bacterial P450 Mammalian P450 Does a sequence fit a structure ? Buried area % side chain buried with polar atoms Secondary structure Errat non covalently pairs interactions ( CC, CN, CO, NN, NO, OO ) 9 residue sliding window Strobl (30 compounds ) Docking Software: GOLD 2.0 Genetic algorithm ?Full ligand flexibility partial protein flexibility ?Energy functions partly based on