ИСТИНА

Pharmacokinetic properties and toxicity of potential drug compounds (ADMET properties: absorption, distribution, metabolism, excretion, toxicity) critically affect their efficacy, pharmacological profile, administration protocol and safety. Thus, the optimization of these properties is an important aspect of drug discovery and development, and the ability to predict them for new structures can substantially improve the speed and efficiency of such optimization. We have developed a general methodology for the prediction of ADMET parameters based on the application of fragmental descriptors and artificial neural networks to extensive and verified experimental data sets. The models built by us are implemented in a web application available on the Internet (http://qsar.chem.msu.ru/admet/). It supports convenient prediction of important properties (in particular, lipophilicity, blood-brain barrier permeability, intestinal absorption, plasma protein binding, mutagenicity, cardiotoxicity, aromatic hydrocarbon receptor binding, cytotoxicity, etc.) as well as qualitative and semi-quantitative estimation of their suitability for drug-like compounds. This integrated prediction system may be used in the research in various areas of medicinal chemistry and pharmacology.