ADMETlab: a Platform for Systematic ADMET Evaluation Based on a Comprehensively Collected ADMET Database

Overview

Journal J Cheminform

Publisher Biomed Central

Specialty Chemistry

Date 2018 Jun 27

PMID 29943074

Citations 180

Authors

Jie Dong

Ning-Ning Wang

Zhi-Jiang Yao

Lin Zhang

Yan Cheng

Defang Ouyang

Ai-Ping Lu

Dong-Sheng Cao

Affiliations

Soon will be listed here.

Abstract

Current pharmaceutical research and development (R&D) is a high-risk investment which is usually faced with some unexpected even disastrous failures in different stages of drug discovery. One main reason for R&D failures is the efficacy and safety deficiencies which are related largely to absorption, distribution, metabolism and excretion (ADME) properties and various toxicities (T). Therefore, rapid ADMET evaluation is urgently needed to minimize failures in the drug discovery process. Here, we developed a web-based platform called ADMETlab for systematic ADMET evaluation of chemicals based on a comprehensively collected ADMET database consisting of 288,967 entries. Four function modules in the platform enable users to conveniently perform six types of drug-likeness analysis (five rules and one prediction model), 31 ADMET endpoints prediction (basic property: 3, absorption: 6, distribution: 3, metabolism: 10, elimination: 2, toxicity: 7), systematic evaluation and database/similarity searching. We believe that this web platform will hopefully facilitate the drug discovery process by enabling early drug-likeness evaluation, rapid ADMET virtual screening or filtering and prioritization of chemical structures. The ADMETlab web platform is designed based on the Django framework in Python, and is freely accessible at http://admet.scbdd.com/ .

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