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admetSAR3.0: a comprehensive platform for exploration, prediction and optimization of chemical ADMET properties

Nucleic Acids Research 2024 115 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 75 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Yaxin Gu, Zhuohang Yu, Yimeng Wang, Long Chen, Chaofeng Lou, Chen Yang, Weihua Li, Guixia Liu, Yun Tang

Summary

This paper describes admetSAR3.0, an updated software platform for predicting how chemicals are absorbed, distributed, metabolized, and excreted by the body, as well as their toxicity. While not specifically about microplastics, the tool can assess the safety of chemicals found in plastics, including plastic additives and breakdown products. The platform now covers 119 endpoints and includes environmental and cosmetic risk assessments.

Body Systems

Absorption, distribution, metabolism, excretion and toxicity (ADMET) properties play a crucial role in drug discovery and chemical safety assessment. Built on the achievements of admetSAR and its successor, admetSAR2.0, this paper introduced the new version of the series, admetSAR3.0, as a comprehensive platform for chemical ADMET assessment, including search, prediction and optimization modules. In the search module, admetSAR3.0 hosted over 370 000 high-quality experimental ADMET data for 104 652 unique compounds, and supplemented chemical structure similarity search function to facilitate read-across. In the prediction module, we introduced comprehensive ADMET endpoints and two new sections for environmental and cosmetic risk assessments, empowering admetSAR3.0 to provide prediction for 119 endpoints, more than double numbers compared to the previous version. Furthermore, the advanced multi-task graph neural network framework offered robust and reliable support for ADMET prediction. In particular, a module named ADMETopt was added to automatically optimize the ADMET properties of query molecules through transformation rules or scaffold hopping. Finally, admetSAR3.0 provides user-friendly interfaces for multiple types of input data, such as SMILES string, chemical structure and batch molecule file, and supports various output types, including digital, chart displays and file downloads. In summary, admetSAR3.0 is anticipated to be a valuable and powerful tool in drug discovery and chemical safety assessment at http://lmmd.ecust.edu.cn/admetsar3/.

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