{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T21:07:42Z","timestamp":1791925662330,"version":"4.3.4"},"reference-count":31,"publisher":"Public Library of Science (PLoS)","issue":"5","license":[{"start":{"date-parts":[[2024,5,10]],"date-time":"2024-05-10T00:00:00Z","timestamp":1715299200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81974300"],"award-info":[{"award-number":["81974300"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"China Postdoctoral Science Foundation COVID-19 Prevention Special Project","award":["2020T130151ZX"],"award-info":[{"award-number":["2020T130151ZX"]}]},{"DOI":"10.13039\/100014717","name":"National Outstanding Youth Science Fund Project of National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81902012"],"award-info":[{"award-number":["81902012"]}],"id":[{"id":"10.13039\/100014717","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COVID-19 disease, which represents a new life-threatening disaster. Regarding viral infection, many therapeutics have been investigated to alleviate the epidemiology such as vaccines and receptor decoys. However, the continuous mutating coronavirus, especially the variants of Delta and Omicron, are tended to invalidate the therapeutic biological product. Thus, it is necessary to develop molecular entities as broad-spectrum antiviral drugs. Coronavirus replication is controlled by the viral 3-chymotrypsin-like cysteine protease (3CLpro) enzyme, which is required for the virus\u2019s life cycle. In the cases of severe acute respiratory syndrome coronavirus (SARS-CoV) and middle east respiratory syndrome coronavirus (MERS-CoV), 3CLpro has been shown to be a promising therapeutic development target. Here we proposed an attention-based deep learning framework for molecular graphs and sequences, training from the BindingDB 3CLpro dataset (114,555 compounds). After construction of such model, we conducted large-scale screening the <jats:italic>in vivo\/vitro<\/jats:italic> dataset (276,003 compounds) from Zinc Database and visualize the candidate compounds with attention score. geometric-based affinity prediction was employed for validation. Finally, we established a 3CLpro-specific deep learning framework, namely GraphDPI-3CL (AUROC: 0.958) achieved superior performance beyond the existing state of the art model and discovered 10 molecules with a high binding affinity of 3CLpro and superior binding mode.<\/jats:p>","DOI":"10.1371\/journal.pone.0299696","type":"journal-article","created":{"date-parts":[[2024,5,10]],"date-time":"2024-05-10T17:42:07Z","timestamp":1715362927000},"page":"e0299696","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":6,"title":["Predicting drug\u2013Protein interaction with deep learning framework for molecular graphs and sequences: Potential candidates against SAR-CoV-2"],"prefix":"10.1371","volume":"19","author":[{"given":"Weian","family":"Du","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rong","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Boning","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Si","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yufeng","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huaiqiu","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8063-8749","authenticated-orcid":true,"given":"Ge","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2024,5,10]]},"reference":[{"issue":"1","key":"pone.0299696.ref001","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s42003-020-01577-x","article-title":"Identification of 3-chymotrypsin like protease (3CLPro) inhibitors as potential anti-SARS-CoV-2 agents","volume":"4","author":"V. Mody","year":"2021","journal-title":"Communications biology"},{"issue":"7811","key":"pone.0299696.ref002","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1038\/s41586-020-2223-y","article-title":"Structure of Mpro from SARS-CoV-2 and discovery of its inhibitors","volume":"582","author":"Z. Jin","year":"2020","journal-title":"Nature"},{"key":"pone.0299696.ref003","doi-asserted-by":"crossref","first-page":"2098","DOI":"10.3389\/fmicb.2020.02098","article-title":"Emerging molecular prospective of SARS-CoV-2: Feasible nanotechnology based detection and inhibition","author":"S. Patra","year":"2020","journal-title":"Frontiers in Microbiology"},{"issue":"7","key":"pone.0299696.ref004","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1016\/j.tim.2016.03.010","article-title":"Improving Viral Protease Inhibitors to Counter Drug Resistance","volume":"24","author":"N. Kurt Yilmaz","year":"2016","journal-title":"Trends in microbiology"},{"issue":"557","key":"pone.0299696.ref005","doi-asserted-by":"crossref","first-page":"eabc5332","DOI":"10.1126\/scitranslmed.abc5332","article-title":"3C-like protease inhibitors block coronavirus replication in vitro and improve survival in MERS-CoV\u2013infected mice","volume":"12","author":"A.D. Rathnayake","year":"2020","journal-title":"Science Translational Medicine"},{"issue":"7811","key":"pone.0299696.ref006","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1038\/s41586-020-2223-y","article-title":"Structure of Mpro from SARS-CoV-2 and discovery of its inhibitors","volume":"582","author":"Z. Jin","year":"2020","journal-title":"Nature"},{"issue":"9","key":"pone.0299696.ref007","doi-asserted-by":"crossref","first-page":"2806","DOI":"10.3390\/molecules26092806","article-title":"In silico studies of some isoflavonoids as potential candidates against COVID-19 targeting human ACE2 (hACE2) and viral main protease (Mpro)","volume":"26","author":"M.S. Alesawy","year":"2021","journal-title":"Molecules"},{"issue":"1","key":"pone.0299696.ref008","doi-asserted-by":"crossref","first-page":"17796","DOI":"10.1038\/s41598-022-22668-1","article-title":"Characterization of the binding of MRTX1133 as an avenue for the discovery of potential KRASG12D inhibitors for cancer therapy","volume":"12","author":"A.R. Issahaku","year":"2022","journal-title":"Scientific Reports"},{"issue":"1","key":"pone.0299696.ref009","doi-asserted-by":"crossref","first-page":"8656","DOI":"10.1038\/s41598-023-35161-0","article-title":"Dual synergistic inhibition of COX and LOX by potential chemicals from Indian daily spices investigated through detailed computational studies","volume":"13","author":"M. Rudrapal","year":"2023","journal-title":"Scientific Reports"},{"issue":"24","key":"pone.0299696.ref010","doi-asserted-by":"crossref","first-page":"e202300277","DOI":"10.1002\/slct.202300277","article-title":"Discovery of Potential KRAS\u2010SOS1 Inhibitors from South African Natural Compounds: An In silico Approach","volume":"8","author":"A.R. Issahaku","year":"2023","journal-title":"ChemistrySelect"},{"issue":"5","key":"pone.0299696.ref011","doi-asserted-by":"crossref","first-page":"e202103908","DOI":"10.1002\/slct.202103908","article-title":"Design, Synthesis, Molecular Docking, Molecular Dynamics and In Vivo Antimalarial Activity of New Dipeptide\u2010Sulfonamides","volume":"7","author":"J.A. Ezugwu","year":"2022","journal-title":". ChemistrySelect"},{"key":"pone.0299696.ref012","doi-asserted-by":"crossref","first-page":"130862","DOI":"10.1016\/j.molstruc.2021.130862","article-title":"Toward a treatment of antibacterial and antifungal infections: Design, synthesis and in vitro activity of novel arylhydrazothiazolylsulfonamides analogues and their insight of DFT, docking and molecular dynamic simulations","volume":"1243","author":"I.M. Othman","year":"2021","journal-title":"Journal of Molecular Structure"},{"key":"pone.0299696.ref013","doi-asserted-by":"crossref","first-page":"1185236","DOI":"10.3389\/fnut.2023.1185236","article-title":"Utilizing Andrographis paniculata leaves and roots by effective usage of the bioactive andrographolide and its nanodelivery: investigation of antikindling and antioxidant activities through in silico and in vivo studies","volume":"10","author":"R. Baru Venkata","year":"2023","journal-title":"Frontiers in Nutrition"},{"issue":"D1","key":"pone.0299696.ref014","doi-asserted-by":"crossref","first-page":"D439","DOI":"10.1093\/nar\/gkab1061","article-title":"AlphaFold Protein Structure Database: Massively expanding the structural coverage of protein-sequence space with high-accuracy models","volume":"50","author":"M. Varadi","year":"2022","journal-title":"Nucleic acids research"},{"issue":"7873","key":"pone.0299696.ref015","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1038\/s41586-021-03819-2","article-title":"Highly accurate protein structure prediction with AlphaFold","volume":"596","author":"J. Jumper","year":"2021","journal-title":"Nature"},{"key":"pone.0299696.ref016","article-title":"Effective drug-target interaction prediction with mutual interaction neural network","author":"F. Li","year":"2022","journal-title":"Bioinformatics"},{"issue":"4","key":"pone.0299696.ref017","doi-asserted-by":"crossref","first-page":"bbac272","DOI":"10.1093\/bib\/bbac272","article-title":"AttentionSiteDTI: an interpretable graph-based model for drug-target interaction prediction using NLP sentence-level relation classification","volume":"23","author":"M. Yazdani-Jahromi","year":"2022","journal-title":"Briefings in Bioinformatics"},{"issue":"1","key":"pone.0299696.ref018","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.drudis.2020.10.010","article-title":"Artificial intelligence in drug discovery and development","volume":"26","author":"D. Paul","year":"2021","journal-title":"Drug Discovery Today"},{"issue":"1","key":"pone.0299696.ref019","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1177\/0141076818815510","article-title":"Artificial intelligence-enabled healthcare delivery","volume":"112","author":"S. Reddy","year":"2019","journal-title":"Journal of the Royal Society of Medicine"},{"issue":"1","key":"pone.0299696.ref020","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1186\/s13321-020-00456-1","article-title":"An open source chemical structure curation pipeline using RDKit","volume":"12","author":"A.P. Bento","year":"2020","journal-title":"Journal of Cheminformatics"},{"issue":"6","key":"pone.0299696.ref021","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1007\/s10822-010-9349-1","article-title":"Towards the comprehensive, rapid, and accurate prediction of the favorable tautomeric states of drug-like molecules in aqueous solution","volume":"24","author":"J.R. Greenwood","year":"2010","journal-title":"Journal of Computer-Aided Molecular Design"},{"issue":"12","key":"pone.0299696.ref022","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1007\/s10822-007-9133-z","article-title":"Epik: a software program for pKaprediction and protonation state generation for drug-like molecules","volume":"21","author":"J.C. Shelley","year":"2007","journal-title":"Journal of Computer-Aided Molecular Design"},{"issue":"6","key":"pone.0299696.ref023","doi-asserted-by":"crossref","first-page":"2697","DOI":"10.1021\/acs.jcim.0c01489","article-title":"XGraphBoost: extracting graph neural network-based features for a better prediction of molecular properties","volume":"61","author":"D. Deng","year":"2021","journal-title":"Journal of chemical information and modeling"},{"issue":"6","key":"pone.0299696.ref024","doi-asserted-by":"crossref","first-page":"1692","DOI":"10.1039\/C8SC04175J","article-title":"Learning continuous and data-driven molecular descriptors by translating equivalent chemical representations","volume":"10","author":"R. Winter","year":"2019","journal-title":"Chemical science"},{"key":"pone.0299696.ref025","article-title":"Neural message passing for quantum chemistry","author":"J. Gilmer","year":"2017","journal-title":"International conference on machine learning"},{"key":"pone.0299696.ref026","article-title":"Attention is all you need","volume":"30","author":"A. Vaswani","year":"2017","journal-title":"Advances in neural information processing systems"},{"issue":"2","key":"pone.0299696.ref027","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1038\/s42256-020-0152-y","article-title":"Predicting drug\u2013protein interaction using quasi-visual question answering system","volume":"2","author":"S. Zheng","year":"2020","journal-title":"Nature Machine Intelligence"},{"issue":"16","key":"pone.0299696.ref028","doi-asserted-by":"crossref","first-page":"4406","DOI":"10.1093\/bioinformatics\/btaa524","article-title":"TransformerCPI: improving compound\u2013protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments","volume":"36","author":"L. Chen","year":"2020","journal-title":"Bioinformatics"},{"issue":"4","key":"pone.0299696.ref029","first-page":"1","article-title":"Xgboost: extreme gradient boosting","volume":"1","author":"T. Chen","year":"2015","journal-title":"R package version 0.4\u20132"},{"issue":"2","key":"pone.0299696.ref030","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1038\/s41592-019-0666-6","article-title":"Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning","volume":"17","author":"P. Gainza","year":"2020","journal-title":"Nature Methods"},{"key":"pone.0299696.ref031","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1007\/978-1-61779-588-6_10","article-title":"Methods of protein structure comparison","volume":"857","author":"I. Kufareva","year":"2012","journal-title":"Methods in molecular biology (Clifton, N.J.)"}],"container-title":["PLOS ONE"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0299696","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,10]],"date-time":"2024-05-10T17:42:23Z","timestamp":1715362943000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0299696"}},"subtitle":[],"editor":[{"given":"Gurudeeban","family":"Selvaraj","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2024,5,10]]},"references-count":31,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2024,5,10]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0299696","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,10]]}}}