Jump to main content
Jump to site search


ADMET-score - A Comprehensive Scoring Function for Evaluation of Chemical Drug-likeness

Abstract

Chemical absorption, distribution, metabolism, excretion, and toxicity (ADMET), play key roles in drug discovery and development. A high-quality drug candidate should not only have sufficient efficacy against the therapeutic target, but also show appropriate ADMET properties at a therapeutic dose. A lot of in silico models are hence developed for prediction of chemical ADMET properties. However, it is still not easy to evaluate the drug-likeness of compounds in terms of so many ADMET properties. In this study, we proposed a scoring function named ADMET-score to evaluate drug-likeness of a compound. The scoring function was defined on the basis of 18 ADMET properties predicted via our web server admetSAR. The weight of each property in ADMET-score was determined by three parameters: the accuracy rate of model, the importance of the endpoint in the process of pharmacokinetics, and the beneficial distribution in oral drugs. The FDA-approved drugs from DrugBank, the small molecules from ChEMBL and the old drugs withdrawn from the market due to safety concerns were used to evaluate the performance of ADMET-score. The indices of arithmetic mean and p-value showed that ADMET-score among the three data sets differed significantly. Furthermore, we learned that there was no obvious linear correlation between ADMET-score and QED (quantitative estimate of drug-likeness). These results suggested that ADMET-score would be a comprehensive index to evaluate chemical drug-likeness, and might be helpful for users to select appropriate drug candidates for further development.

Back to tab navigation

Supplementary files

Publication details

The article was received on 20 Sep 2018, accepted on 29 Nov 2018 and first published on 30 Nov 2018


Article type: Research Article
DOI: 10.1039/C8MD00472B
Citation: Med. Chem. Commun., 2018, Accepted Manuscript
  •   Request permissions

    ADMET-score - A Comprehensive Scoring Function for Evaluation of Chemical Drug-likeness

    L. Guan, H. Yang, Y. Cai, L. Sun, P. Di, W. Li, G. Liu and Y. Tang, Med. Chem. Commun., 2018, Accepted Manuscript , DOI: 10.1039/C8MD00472B

Search articles by author

Spotlight

Advertisements