ToxME: Integrated in silico approach to understand polymorphism and drug side effects related to drug metabolizing enzymes – ToxME

Discovery of new drugs faces formidable challenges including the high complexity of many diseases, the increasing costs of new treatment discovery as well as the safety and effectiveness of newly introduced medicines. During the last 30 years, more than 30 drugs have been withdrawn from the market due to severe adverse drug reactions. Thus, prediction of drug side effects early in the drug discovery process might help to reduce the attrition and to increase the safety of drugs. Current directives of the European Commission require shifting the paradigm for drugs/xenobiotics toxicity prediction toward application of novel in silico and in vitro approaches in order to significantly reduce animal studies, the latter posing ethical problems and questions on the reliability of animal models due to differences between human and animal molecular mechanisms.

In this direction, our project focuses on developing a novel web-based platform ToxME for an integrated in silico prediction of chemicals and drugs toxicity related to interactions with drug metabolizing enzymes (DMEs) and their polymorphisms and will contribute for novel mechanistic understanding of the elucidated phenomena. Thanks to the highly complementary expertise of the partners, we will develop innovative in silico methodology that will be experimentally validated by in vitro assays and structural X-ray and NMR studies. To achieve these objectives, we will perform comprehensive studies of key isoforms and polymorphic alleles (specified in the work program) of DMEs: cytochrome P450 (CYP) and the conjugation enzymes sulfotransferase (SULT). Prediction of binding energies for diverse drugs and chemical compounds will be performed for CYP and SULT by the Partner 1 (the coordinator team) in order to predict putative DMEs inhibitors. In addition, we will develop automated in silico protocols to predict Sites of Metabolism (SoM) of CYP and SULT substrates. A particularly innovative part of this project is dedicated to gain mechanistic insights in the impact of genetic polymorphisms of CYP and SULT on drug metabolism, which are critical for efficacy or toxicity of (pro)drugs and their metabolites, and thus for modern pharmacogenomics and personalized medications related to drug metabolism. All together, the computational modeling studies will ensure establishing of an integrated in silico approach for prediction of xenobiotics and drug toxicity related to DMEs that will be accessible via a web-based software application, freely accessible for academics and commercial for private companies. The performance of the developed approach will be validated by in vitro assays for compounds/drugs predicted to be inhibitors or substrates of the studied isoforms of CYP and SULT (Partners 2 and 3). Moreover, we will perform crystallographic and NMR studies (Partners 3, 4) to solve structures of polymorphic isoenzymes CYP and SULT in complexes with several drugs that will increase our mechanistic understanding of drugs-DME interactions. To the best of our knowledge, this will be the first web-based platform for in silico prediction of chemicals toxicity and drug side effects and efficacy specifically related to DMEs and based on 3D structural knowledge for CYP and SULT and their polymorphisms.