دورية أكاديمية
PGBind: pocket-guided explicit attention learning for protein-ligand docking.
العنوان: | PGBind: pocket-guided explicit attention learning for protein-ligand docking. |
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المؤلفون: | Shen A; Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, 131 Dong'an Road, Shanghai 200032, China.; Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention, Fudan University, 131 Dong'an Road, Shanghai 200032, China., Yuan M; Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, 131 Dong'an Road, Shanghai 200032, China.; Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention, Fudan University, 131 Dong'an Road, Shanghai 200032, China., Ma Y; Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, 131 Dong'an Road, Shanghai 200032, China.; Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention, Fudan University, 131 Dong'an Road, Shanghai 200032, China., Du J; Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, 131 Dong'an Road, Shanghai 200032, China.; Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention, Fudan University, 131 Dong'an Road, Shanghai 200032, China., Wang M; Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, 131 Dong'an Road, Shanghai 200032, China.; Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention, Fudan University, 131 Dong'an Road, Shanghai 200032, China. |
المصدر: | Briefings in bioinformatics [Brief Bioinform] 2024 Jul 25; Vol. 25 (5). |
نوع المنشور: | Journal Article |
اللغة: | English |
بيانات الدورية: | Publisher: Oxford University Press Country of Publication: England NLM ID: 100912837 Publication Model: Print Cited Medium: Internet ISSN: 1477-4054 (Electronic) Linking ISSN: 14675463 NLM ISO Abbreviation: Brief Bioinform Subsets: MEDLINE |
أسماء مطبوعة: | Publication: Oxford : Oxford University Press Original Publication: London ; Birmingham, AL : H. Stewart Publications, [2000- |
مواضيع طبية MeSH: | Ligands* , Proteins*/chemistry , Proteins*/metabolism , Drug Discovery*, Algorithms ; Binding Sites ; Computational Biology/methods ; Deep Learning ; Molecular Docking Simulation ; Protein Binding ; Protein Conformation |
مستخلص: | As more and more protein structures are discovered, blind protein-ligand docking will play an important role in drug discovery because it can predict protein-ligand complex conformation without pocket information on the target proteins. Recently, deep learning-based methods have made significant advancements in blind protein-ligand 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. (© The Author(s) 2024. Published by Oxford University Press.) |
References: | Nucleic Acids Res. 2010 Jul;38(Web Server issue):W469-73. (PMID: 20513649) ACS Chem Neurosci. 2021 Jun 16;12(12):2133-2142. (PMID: 34081851) J Chem Inf Model. 2023 Jul 24;63(14):4355-4363. (PMID: 37386792) Nat Rev Drug Discov. 2017 Jan;16(1):19-34. (PMID: 27910877) Bioinformatics. 2023 Dec 1;39(12):. (PMID: 38019955) J Chem Inf Model. 2022 Nov 14;62(21):5069-5079. (PMID: 34374539) Genome Inform. 2004;15(2):31-41. (PMID: 15706489) Nat Rev Drug Discov. 2006 Dec;5(12):993-6. (PMID: 17139284) IEEE/ACM Trans Comput Biol Bioinform. 2022 Jan-Feb;19(1):407-417. (PMID: 33360998) Sci Rep. 2017 Nov 13;7(1):15451. (PMID: 29133831) Bioinformatics. 2017 Oct 01;33(19):3036-3042. (PMID: 28575181) Bioinformatics. 2016 Oct 15;32(20):3142-3149. (PMID: 27354702) Nat Comput Sci. 2022 Dec;2(12):775-776. (PMID: 38177394) J Cell Mol Med. 2009 Feb;13(2):238-48. (PMID: 19183238) J Cheminform. 2021 Jun 9;13(1):43. (PMID: 34108002) J Biomol Struct Dyn. 2022;40(24):13472-13481. (PMID: 34641761) IEEE/ACM Trans Comput Biol Bioinform. 2023 Sep-Oct;20(5):3314-3321. (PMID: 37040253) BMC Bioinformatics. 2009 Jun 02;10:168. (PMID: 19486540) Acc Chem Res. 2017 Feb 21;50(2):302-309. (PMID: 28182403) Nucleic Acids Res. 2000 Jan 1;28(1):235-42. (PMID: 10592235) J Med Chem. 2004 Mar 25;47(7):1739-49. (PMID: 15027865) J Cheminform. 2015 May 20;7:20. (PMID: 26052348) J Chem Inf Model. 2013 Aug 26;53(8):1893-904. (PMID: 23379370) Nat Methods. 2020 Feb;17(2):184-192. (PMID: 31819266) Drug Discov Today. 2024 Jul;29(7):104024. (PMID: 38759948) |
معلومات مُعتمدة: | 23S41900400 Science and Technology Innovation Plan Of Shanghai Science and Technology Commission; FD-AI4S04183 Fudan University Science Intelligence Special Fund |
فهرسة مساهمة: | Keywords: AI for science; drug discovery; protein–ligand blind docking; protein–ligand docking |
المشرفين على المادة: | 0 (Ligands) 0 (Proteins) |
تواريخ الأحداث: | Date Created: 20240918 Date Completed: 20240918 Latest Revision: 20240925 |
رمز التحديث: | 20240925 |
مُعرف محوري في PubMed: | PMC11410380 |
DOI: | 10.1093/bib/bbae455 |
PMID: | 39293803 |
قاعدة البيانات: | MEDLINE |
تدمد: | 1477-4054 |
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DOI: | 10.1093/bib/bbae455 |