{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T21:01:34Z","timestamp":1785272494627,"version":"3.55.0"},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T00:00:00Z","timestamp":1648512000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2017YFC1104400"],"award-info":[{"award-number":["2017YFC1104400"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,13]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>In the process of discovery and optimization of lead compounds, it is difficult for non-expert pharmacologists to intuitively determine the contribution of substructure to a particular property of a molecule.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In this work, we develop a user-friendly web service, named interpretable-absorption, distribution, metabolism, excretion and toxicity (ADMET), which predict 59 ADMET-associated properties using 90 qualitative classification models and 28 quantitative regression models based on graph convolutional neural network and graph attention network algorithms. In interpretable-ADMET, there are 250\u00a0729 entries associated with 59 kinds of ADMET-associated properties for 80\u00a0167 chemical compounds. In addition to making predictions, interpretable-ADMET provides interpretation models based on gradient-weighted class activation map for identifying the substructure, which is important to the particular property. Interpretable-ADMET also provides an optimize module to automatically generate a set of novel virtual candidates based on matched molecular pair rules. We believe that interpretable-ADMET could serve as a useful tool for lead optimization in drug discovery.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>Interpretable-ADMET is available at http:\/\/cadd.pharmacy.nankai.edu.cn\/interpretableadmet\/.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac192","type":"journal-article","created":{"date-parts":[[2022,3,28]],"date-time":"2022-03-28T19:21:53Z","timestamp":1648495313000},"page":"2863-2871","source":"Crossref","is-referenced-by-count":87,"title":["Interpretable-ADMET: a web service for ADMET prediction and optimization based on deep neural representation"],"prefix":"10.1093","volume":"38","author":[{"given":"Yu","family":"Wei","sequence":"first","affiliation":[{"name":"State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University , Tianjin 300353, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shanshan","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University , Tianjin 300353, China"},{"name":"Platform of Pharmaceutical Intelligence, Tianjin International Joint Academy of Biomedicine , Tianjin 300457, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhonglin","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University , Tianjin 300353, China"},{"name":"Platform of Pharmaceutical Intelligence, Tianjin International Joint Academy of Biomedicine , Tianjin 300457, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziwei","family":"Wan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University , Tianjin 300353, China"},{"name":"Platform of Pharmaceutical Intelligence, Tianjin International Joint Academy of Biomedicine , Tianjin 300457, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6974-0072","authenticated-orcid":false,"given":"Jianping","family":"Lin","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University , Tianjin 300353, China"},{"name":"Platform of Pharmaceutical Intelligence, Tianjin International Joint Academy of Biomedicine , Tianjin 300457, China"},{"name":"Biodesign Center, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences , Tianjin 300308, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,3,29]]},"reference":[{"key":"2023020109052874600_btac192-B1","doi-asserted-by":"crossref","first-page":"2719","DOI":"10.1021\/jm901137j","article-title":"New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays","volume":"53","author":"Baell","year":"2010","journal-title":"J. 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