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Validation of Model of Cytochrome P450 2D6: An in Silico Tool for Predicting Metabolism 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.
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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
Oxidation of >50 drugs Inhibited by drugs Importance of Cyp 2D6 Analgesics (pain killers) Quinidine (heart rhythm disturbance) Cytochrome P450 2D6 Beta Blockers (cardiovascular diseases) fluoxertine (depression)
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) Bacterial P450 Mammalian P450
Model Validation 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
Screened Available Databases Ekins ( 21 compounds ) • Docking Software: GOLD 2.0 • Genetic algorithm • •Full ligand flexibility partial protein flexibility • •Energy functions partly based on conformational and non-bonded contact information from the CSD Strobl (30 compounds ) 1 ring system r2 = 0.36 12 ring systems r2 = 0.56
Creating an Additional Dataset NCI database (compounds tested for treating cancer) Weight ~ Ekins & Strobl datasets < 4 Ring Systems Availability 33 Compunds Basic Nitrogen & Aromatic Group
Consistency with known inhibition measurements AMMC demethylase Cyp450 2D6 Small Molecule Inhibition Inhibition Ekins / Strobl AMMC
Predicting inhibition using Docking Cutoffs: IC50 < 10 µM = inhibitor -30 kJ/mol = predicted inhibitor Predictions: 13 correct 7 false positives
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 ?
