Davies Mark, Dedman Nathan, Hersey Anne, Papadatos George, Hall Matthew D, Cucurull-Sanchez Lourdes, Jeffrey Phil, Hasan Samiul, Eddershaw Peter J, Overington John P
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage SG1 2NY and Pfizer Ltd., Granta Park, Great Abington, Cambridge CB21 6GP, UK.
Bioinformatics. 2015 May 15;31(10):1695-7. doi: 10.1093/bioinformatics/btv010. Epub 2015 Jan 8.
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.
ADME SARfari是一个免费的网络资源,可用于对药物处置基因进行比较分析。它通过整合多个公开可用的数据源来实现这一点,这些数据源随后被用于为药物代谢研究人员构建数据挖掘服务、预测工具和可视化。数据包括小分子与负责分子代谢和转运的ADME(吸收、分布、代谢和排泄)蛋白的相互作用;可用的药代动力学(PK)数据;临床前模型物种和人类的ADME相关分子靶点的蛋白质序列;直系同源物的比对,包括已知单核苷酸多态性(SNP)的信息以及这些蛋白质的组织分布信息。此外,还开发了计算机模拟模型,使用户能够预测一种新型化合物可能与哪些ADME相关蛋白靶点相互作用。