Prediction methods and databases within chemoinformatics:: emphasis on drugs and drug candidates

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.