{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T13:28:13Z","timestamp":1786368493178,"version":"build-2736575974"},"reference-count":51,"publisher":"American Chemical Society (ACS)","issue":"15","license":[{"start":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T00:00:00Z","timestamp":1784505600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T00:00:00Z","timestamp":1784505600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T00:00:00Z","timestamp":1784505600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-045"}],"funder":[{"name":"Lingang Laboratory","award":["25Z670104275"],"award-info":[{"award-number":["25Z670104275"]}]},{"name":"Beijing Life Science Academy","award":["2024200CD0190"],"award-info":[{"award-number":["2024200CD0190"]}]},{"name":"National Science and Technology Major Project for Significant New Drugs Development","award":["2025ZD1801102"],"award-info":[{"award-number":["2025ZD1801102"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China (NSFC)","doi-asserted-by":"crossref","award":["22494694"],"award-info":[{"award-number":["22494694"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,8,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Hepatotoxicity represents a major adverse outcome of chemical exposure, as the liver plays a central role in xenobiotic metabolism and detoxification. Accurate prediction of hepatotoxicity is therefore essential for drug development and chemical safety assessment. Computational methods provide an efficient and ethical alternative for assessing hepatotoxicity before experimental validation. To address this need, we developed DeepHeptox, a deep learning model based on Graph Attention Networks (GAT) for multi-endpoint hepatotoxicity prediction, covering hepatitis, jaundice, elevated liver enzymes, hepatocellular injury, hepatic fibrosis, hepatomegaly, and cholestasis. DeepHeptox achieved area under the ROC curve (AUC) values exceeding 0.87 and accuracy (ACC) above 0.80 for both overall and endpoint-specific predictions on the test set. Our approach enables both the identification of structural alerts (SAs) via Klekota\u2013Roth fingerprint (KRFP) analysis and the visualization of molecular substructure importance for hepatotoxicity predictions through GNNExplainer. A user-friendly web server is provided for interactive prediction and visualization. DeepHeptox offers a practical tool for early stage toxicity screening in drug development and chemical safety evaluation.<\/jats:p>","DOI":"10.1021\/acs.jcim.6c01434","type":"journal-article","created":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T06:02:46Z","timestamp":1784527366000},"page":"8968-8979","source":"Crossref","is-referenced-by-count":0,"title":["DeepHeptox: An\nInterpretable Deep Learning Model for\nMulti-Endpoint Hepatotoxicity Prediction of Chemical Compounds"],"prefix":"10.1021","volume":"66","author":[{"given":"Ming","family":"Luo","sequence":"first","affiliation":[{"name":"Southern Medical University , , ,","place":["Guangzhou, China, 510515"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qinghua","family":"Wang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University , , 800 Dongchuan Road ,","place":["Shanghai, China, 200240"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuxuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University , , 800 Dongchuan Road ,","place":["Shanghai, China, 200240"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengli","family":"Li","sequence":"additional","affiliation":[{"name":"Fuyang Cancer Hospital , , ,","place":["Fuyang, China, 236000"]},{"name":"Anhui Medical University , , ,","place":["Hefei, China, 230032"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7205-9202","authenticated-orcid":true,"given":"Ao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University , , 800 Dongchuan Road ,","place":["Shanghai, China, 200240"]},{"name":"Southern Medical University , , ,","place":["Guangzhou, China, 510515"]},{"name":"Shanghai Jiao Tong University , , 800 Dongchuan Road , ,","place":["Shanghai, China, 200240"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5963-9779","authenticated-orcid":true,"given":"Yaxue","family":"Zhao","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University , , 800 Dongchuan Road ,","place":["Shanghai, China, 200240"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,7,20]]},"reference":[{"issue":"16","key":"2026081008100269300_cit1","doi-asserted-by":"publisher","first-page":"2413405","DOI":"10.1002\/advs.202413405","article-title":"Machine Learning-Enabled\nDrug-Induced Toxicity Prediction","volume":"12","author":"Bai","year":"2025","journal-title":"Adv. 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