Motivation: ADME SARfari is a freely available web resource that enables comparative analyses of drug-disposition genes. It does so by integrating a number of publicly available data sources, which have subsequently been used to build data mining services, predictive tools and visualizations for drug metabolism researchers. The data include the interactions of small molecules with ADME (absorption, distribution, metabolism and excretion) proteins responsible for the metabolism and transport of molecules; available pharmacokinetic (PK) data; protein sequences of ADME-related molecular targets for pre-clinical model species and human; alignments of the orthologues including information on known SNPs (Single Nucleotide Polymorphism) and information on the tissue distribution of these proteins. In addition, in silico models have been developed, which enable users to predict which ADME relevant protein targets a novel compound is likely to interact with.#R##N##R##N#Availability and implementation: https://www.ebi.ac.uk/chembl/admesarfari#R##N##R##N#Contact: ku.ca.ibe@opj#R##N##R##N#Supplementary information: Supplementary data are available at Bioinformatics online.
['Mark Davies', 'Nathan Dedman', 'Anne Hersey', 'George Papadatos', 'Matthew D. Hall', 'Lourdes Cucurull-Sanchez', 'Phil Jeffrey', 'Samiul Hasan', 'Peter J. Eddershaw', 'John P. Overington']
ADME SARfari: comparative genomics of drug metabolizing systems