{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T03:22:20Z","timestamp":1782703340307,"version":"3.54.5"},"reference-count":43,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2024,9,18]],"date-time":"2024-09-18T00:00:00Z","timestamp":1726617600000},"content-version":"vor","delay-in-days":55,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100018625","name":"Science and Technology Innovation Plan Of Shanghai Science and Technology Commission","doi-asserted-by":"publisher","award":["23S41900400"],"award-info":[{"award-number":["23S41900400"]}],"id":[{"id":"10.13039\/501100018625","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fudan University Science Intelligence Special Fund","award":["FD-AI4S04183"],"award-info":[{"award-number":["FD-AI4S04183"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,25]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>As more and more protein structures are discovered, blind protein\u2013ligand docking will play an important role in drug discovery because it can predict protein\u2013ligand complex conformation without pocket information on the target proteins. Recently, deep learning-based methods have made significant advancements in blind protein\u2013ligand docking, but their protein features are suboptimal because they do not fully consider the difference between potential pocket regions and non-pocket regions in protein feature extraction. In this work, we propose a pocket-guided strategy for guiding the ligand to dock to potential docking regions on a protein. To this end, we design a plug-and-play module to enhance the protein features, which can be directly incorporated into existing deep learning-based blind docking methods. The proposed module first estimates potential pocket regions on the target protein and then leverages a pocket-guided attention mechanism to enhance the protein features. Experiments are conducted on integrating our method with EquiBind and FABind, and the results show that their blind-docking performances are both significantly improved and new start-of-the-art performance is achieved by integration with FABind.<\/jats:p>","DOI":"10.1093\/bib\/bbae455","type":"journal-article","created":{"date-parts":[[2024,9,18]],"date-time":"2024-09-18T22:37:26Z","timestamp":1726699046000},"source":"Crossref","is-referenced-by-count":6,"title":["PGBind: pocket-guided explicit attention learning for protein\u2013ligand docking"],"prefix":"10.1093","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-1937-6855","authenticated-orcid":false,"given":"Ao","family":"Shen","sequence":"first","affiliation":[{"name":"Digital Medical Research Center , School of Basic Medical Sciences, , 131 Dong\u2019an Road, Shanghai 200032 , China"},{"name":"Fudan University , School of Basic Medical Sciences, , 131 Dong\u2019an Road, Shanghai 200032 , China"},{"name":"Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention, Fudan University , 131 Dong\u2019an Road, Shanghai 200032 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1322-7530","authenticated-orcid":false,"given":"Mingzhi","family":"Yuan","sequence":"additional","affiliation":[{"name":"Digital Medical Research Center , School of Basic Medical Sciences, , 131 Dong\u2019an Road, Shanghai 200032 , China"},{"name":"Fudan University , School of Basic Medical Sciences, , 131 Dong\u2019an Road, Shanghai 200032 , China"},{"name":"Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention, Fudan University , 131 Dong\u2019an Road, Shanghai 200032 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-7335-785X","authenticated-orcid":false,"given":"Yingfan","family":"Ma","sequence":"additional","affiliation":[{"name":"Digital Medical Research Center , School of Basic Medical Sciences, , 131 Dong\u2019an Road, Shanghai 200032 , China"},{"name":"Fudan University , School of Basic Medical Sciences, , 131 Dong\u2019an Road, Shanghai 200032 , China"},{"name":"Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention, Fudan University , 131 Dong\u2019an Road, Shanghai 200032 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Du","sequence":"additional","affiliation":[{"name":"Digital Medical Research Center , School of Basic Medical Sciences, , 131 Dong\u2019an Road, Shanghai 200032 , China"},{"name":"Fudan University , School of Basic Medical Sciences, , 131 Dong\u2019an Road, Shanghai 200032 , China"},{"name":"Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention, Fudan University , 131 Dong\u2019an Road, Shanghai 200032 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9255-3897","authenticated-orcid":false,"given":"Manning","family":"Wang","sequence":"additional","affiliation":[{"name":"Digital Medical Research Center , School of Basic Medical Sciences, , 131 Dong\u2019an Road, Shanghai 200032 , China"},{"name":"Fudan University , School of Basic Medical Sciences, , 131 Dong\u2019an Road, Shanghai 200032 , China"},{"name":"Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention, Fudan University , 131 Dong\u2019an Road, Shanghai 200032 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,9,18]]},"reference":[{"key":"2024091822371996600_ref1","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1109\/TCBB.2020.3046945","article-title":"Deep learning in drug design: Protein-ligand binding affinity 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