admetSAR 2.0: web-service for prediction and optimization of chemical ADMET properties

Hongbin Yang; Chaofeng Lou; Lixia Sun; Jie Li; Yingchun Cai; Zhuang Wang; Weihua Li; Guixia Liu; Yun Tang

doi:10.1093/bioinformatics/bty707

admetSAR 2.0: web-service for prediction and optimization of chemical ADMET properties

Bioinformatics. 2019 Mar 15;35(6):1067-1069. doi: 10.1093/bioinformatics/bty707.

Authors

Hongbin Yang¹, Chaofeng Lou¹, Lixia Sun¹, Jie Li¹, Yingchun Cai¹, Zhuang Wang¹, Weihua Li¹, Guixia Liu¹, Yun Tang¹

Affiliation

¹ Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai, China.

PMID: 30165565
DOI: 10.1093/bioinformatics/bty707

Abstract

Summary: admetSAR was developed as a comprehensive source and free tool for the prediction of chemical ADMET properties. Since its first release in 2012 containing 27 predictive models, admetSAR has been widely used in chemical and pharmaceutical fields. This update, admetSAR 2.0, focuses on extension and optimization of existing models with significant quantity and quality improvement on training data. Now 47 models are available for either drug discovery or environmental risk assessment. In addition, we added a new module named ADMETopt for lead optimization based on predicted ADMET properties.

Availability and implementation: Free available on the web at http://lmmd.ecust.edu.cn/admetsar2/.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Drug Discovery*
Software*