MOTIVATION: Cytochromes P450 are the most important class of drug metabolizing enzymes. Prediction of drug metabolism is important in development of new drugs, to understand and reduce adverse drug reactions and to reduce animal testing. RESULTS: SMARTCyp 3.0 is an updated version of our previous web server for prediction of site-of-metabolism for Cytochrome P450-mediated metabolism, now in Python 3 with increased structural coverage and new features. The SMARTCyp program is a first principle-based method using density functional theory determined activation energies for more than 250 molecules to identify the most likely site-of-metabolism. New features include a similarity measure between the query molecule and the model fragment, a new graphical interface and additional parameters expanding the structural coverage of the SMARTCyp program. AVAILABILITY AND IMPLEMENTATION: The SMARTCyp server is freely available for use on the web at smartcyp.sund.ku.dk. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: To gather information about available databases and chemoinformatics methods for prediction of properties relevant to the drug discovery and optimization process. RESULTS: We present an overview of the most important databases with 2-dimensional and 3-dimensional structural information about drugs and drug candidates, and of databases with relevant properties. Access to experimental data and numerical methods for selecting and utilizing these data is crucial for developing accurate predictive in silico models. Many interesting predictive methods for classifying the suitability of chemical compounds as potential drugs, as well as for predicting their physico-chemical and ADMET properties have been proposed in recent years. These methods are discussed, and some possible future directions in this rapidly developing field are described.