ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support

Li Fu(Central South University), Shaohua Shi(Hong Kong Baptist University), Jiacai Yi(National University of Defense Technology), Ningning Wang(Central South University), Yuanhang He(Central South University), Zhenhua Wu(Zhejiang University), Jinfu Peng(Central South University), Youchao Deng(Central South University), Wenxuan Wang(Central South University), Chengkun Wu(National University of Defense Technology), Aiping Lyu(Hong Kong Baptist University), Xiangxiang Zeng(Hunan University), Wentao Zhao(National University of Defense Technology), Tingjun Hou(Zhejiang University), Dongsheng Cao(Central South University)
Nucleic Acids Research
April 4, 2024
Cited by 931Open Access
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Abstract

ADMETlab 3.0 is the second updated version of the web server that provides a comprehensive and efficient platform for evaluating ADMET-related parameters as well as physicochemical properties and medicinal chemistry characteristics involved in the drug discovery process. This new release addresses the limitations of the previous version and offers broader coverage, improved performance, API functionality, and decision support. For supporting data and endpoints, this version includes 119 features, an increase of 31 compared to the previous version. The updated number of entries is 1.5 times larger than the previous version with over 400 000 entries. ADMETlab 3.0 incorporates a multi-task DMPNN architecture coupled with molecular descriptors, a method that not only guaranteed calculation speed for each endpoint simultaneously, but also achieved a superior performance in terms of accuracy and robustness. In addition, an API has been introduced to meet the growing demand for programmatic access to large amounts of data in ADMETlab 3.0. Moreover, this version includes uncertainty estimates in the prediction results, aiding in the confident selection of candidate compounds for further studies and experiments. ADMETlab 3.0 is publicly for access without the need for registration at: https://admetlab3.scbdd.com.


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