Description

Molecular dynamics (MD) simulations essentially act as a computational microscope, modelling the interactions and dynamics between smallmolecules and macromolecules on an atomic level. With this method, it is possible to understand the biological function of chemicals and their targets through their structural motions. Graphics processing unit (GPU) computing is revolutionizing the field of MD, by accelerating calculations to make possible simulations on biological timescales (10s ofns/day) and by expanding the numbers of structures that can be evaluated in atomicresolution in a single run from 10s to 1000s. GPU accelerated MD code is also enabling systematic and rapid testing of improved force fields which opens the gateway to e.g. more accurate and predictive simulations of drug/lipid interactions. In this context, MD simulations may contribute to the upgrading of ChEMBL. ChEMBLhas recently been successfully used as a computational strategy to predict the activity of 656 marketed drugs on 73 unintended ‘side-effect’ targets. Approximately half of the predictions were confirmed, either from proprietary databases unknown to the method orby new experimental assays. To explore relevance, an association metric was developedable to prioritize those new off-targets that explained side effects better than any known target of a given drug, creating a drug-target-adverse drug reaction network. In addition, ChEMBL has also been successfully applied for the automated design of ligands againstprofiles of multiple drug targets. Overall, 800 ligand-target predictions of prospectivelydesigned ligands were tested experimentally, of which 75% were confirmed to be correct. A particular issue in computational chemistry relates to cytochrome P450 enzymes (P450s). The models developed by Optibrium employ a semi-empirical QM approach, parameterized using experimental data and ab initio calculations, to estimate thereactivity of each site to metabolism by P450s. By performing a QM calculation foreach site, this allows not only the most likely sites of metabolism to be identified, but also the proportion and efficiency of metabolism at each site. The results of the QMcalculations are also corrected for the effect of steric and orientation effects on theaccessibility of each site in the binding pockets of the major xenobiotic metabolizing isoforms of P450 (CYP3A4, CYP2D6 and CYP2C9).