{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T18:59:51Z","timestamp":1776279591041,"version":"3.50.1"},"reference-count":45,"publisher":"American Chemical Society (ACS)","issue":"21","license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-045"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Chem. Inf. Model."],"published-print":{"date-parts":[[2025,11,10]]},"DOI":"10.1021\/acs.jcim.5c00950","type":"journal-article","created":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T16:47:08Z","timestamp":1761065228000},"page":"11510-11520","source":"Crossref","is-referenced-by-count":2,"title":["Combining GCN Structural Learning with LLM Chemical Knowledge for Enhanced Virtual Screening"],"prefix":"10.1021","volume":"65","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-1222-2446","authenticated-orcid":true,"given":"Radia","family":"Berreziga","sequence":"first","affiliation":[{"name":"Laboratory of Research in Artificial Intelligence (LRIA), Faculty of Computer Science","place":["Algiers, Algeria"]},{"name":"University of Science and Technology Houari Boumediene (USTHB)","place":["Algiers, Algeria"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammed","family":"Brahimi","sequence":"additional","affiliation":[{"name":"Intelligent Systems Enginnering","place":["Algiers, Algeria"]},{"name":"National School of Artificial Intelligence (ENSIA)","place":["Algiers, Algeria"]},{"name":"Laboratory of Physical Chemistry and Biological Materials, Higher Normal School of Technological Education","place":["Skikda, Algeria"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Khairedine","family":"Kraim","sequence":"additional","affiliation":[{"name":"Laboratory of Physical Chemistry and Biological Materials, Higher Normal School of Technological Education","place":["Skikda, Algeria"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hamid","family":"Azzoune","sequence":"additional","affiliation":[{"name":"Laboratory of Research in Artificial Intelligence (LRIA), Faculty of Computer Science","place":["Algiers, Algeria"]},{"name":"University of Science and Technology Houari Boumediene (USTHB)","place":["Algiers, Algeria"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"316","published-online":{"date-parts":[[2025,10,21]]},"reference":[{"key":"ref1\/cit1","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1186\/s40649-019-0069-y","volume":"6","author":"Zhang S.","year":"2019","journal-title":"Comput. Soc. Networks"},{"key":"ref2\/cit2","first-page":"787","volume-title":"Computer Aided Chemical Engineering","volume":"46","author":"Chang J.-L.","year":"2019"},{"key":"ref3\/cit3","doi-asserted-by":"publisher","DOI":"10.1504\/IJCAT.2020.106571"},{"key":"ref4\/cit4","doi-asserted-by":"crossref","unstructured":"Chen, T.; Guestrin, C. In\n                      Xgboost: A scalable tree boosting system\n                      , Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; Association for Computing Machinery: New York, NY, USA, 2016; pp 785\u2013794.","DOI":"10.1145\/2939672.2939785"},{"key":"ref5\/cit5","doi-asserted-by":"crossref","unstructured":"Chen, T.; Guestrin, C. In\n                      Xgboost: A scalable tree boosting system\n                      , Proceedings of the 22nd acm sigkdd international conference on knowledge discovery and data mining; ACM Digital Library, 2016; pp 785\u2013794.","DOI":"10.1145\/2939672.2939785"},{"key":"ref6\/cit6","unstructured":"Chithrananda, S.; Grand, G.; Ramsundar, B.\n                      Chemberta: Large-scale self-supervised pretraining for molecular property prediction\n                      2020, arXiv:2010.09885. arXiv.org e-Printarchive. https:\/\/arxiv.org\/abs\/2010.09885."},{"key":"ref7\/cit7","unstructured":"ChEMBL Database.\nChembl: A database of bioactive drug-like small molecules. 2024. Accessed: December 27, 2024."},{"key":"ref8\/cit8","unstructured":"Defferrard, M.; Bresson, X.; Vandergheynst, P. In\n                      Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering\n                      , Advances in neural information processing systems; NIPS, 2017."},{"key":"ref9\/cit9","doi-asserted-by":"crossref","unstructured":"Duval, B.; Hao, J.K.; Hernandez, J. C. H.\n                      A memetic algorithm for gene selection and molecular classification of cancer\n                      , Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation; Association for Computing Machinery: New York, NY, USA, 2009; pp 201\u2013208.","DOI":"10.1145\/1569901.1569930"},{"key":"ref10\/cit10","doi-asserted-by":"publisher","DOI":"10.1038\/nbt1068"},{"key":"ref11\/cit11","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecoenv.2021.112120"},{"key":"ref12\/cit12","unstructured":"Guo, Z.; Guo, K.; Nan, B.; Tian, Y.; Iyer, R. G.; Ma, Y.; Wiest, O.; Zhang, X.; Wang, W.; Zhang, C. Graph-based molecular representation learning. 2022, arXiv:2207.04869v3. arXiv.org e-Print archive. https:\/\/arxiv.org\/html\/2207.04869."},{"key":"ref13\/cit13","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/3-540-06399-4_5","volume-title":"New Concepts II","author":"Gutman I.","year":"1973"},{"key":"ref14\/cit14","doi-asserted-by":"publisher","DOI":"10.21873\/cgp.20063"},{"key":"ref15\/cit15","doi-asserted-by":"crossref","first-page":"236","DOI":"10.3389\/fchem.2019.00236","volume":"7","author":"Jenkins J. L.","year":"2019","journal-title":"Front. Chem."},{"key":"ref16\/cit16","unstructured":"Kipf, T. N.; Welling, M. Semi-Supervised Classification with Graph Convolutional Networks. 2017 arXiv:1609.02907. arXiv.org e-Printarchive. https:\/\/arxiv.org\/abs\/1609.02907."},{"key":"ref17\/cit17","doi-asserted-by":"publisher","DOI":"10.1016\/j.omtn.2022.12.014"},{"key":"ref18\/cit18","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-023-05622-4"},{"key":"ref19\/cit19","doi-asserted-by":"crossref","unstructured":"Li, B.; Wang, T.; Nabavi, S. In\n                      Cancer molecular subtype classification by graph convolutional networks on multi-omics data In\n                      , Proceedings of the 12th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics; Association for Computing Machinery: New York, NY, USA, 2021.","DOI":"10.1145\/3459930.3469542"},{"key":"ref20\/cit20","doi-asserted-by":"publisher","DOI":"10.2147\/DDDT.S310163"},{"key":"ref21\/cit21","doi-asserted-by":"publisher","DOI":"10.1038\/nature11159"},{"key":"ref22\/cit22","doi-asserted-by":"publisher","DOI":"10.1126\/science.1075762"},{"issue":"2","key":"ref23\/cit23","first-page":"237","volume":"56","author":"Mauri A.","year":"2006","journal-title":"MATCH Commun. Math. Comput. Chem."},{"key":"ref24\/cit24","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btad519"},{"key":"ref25\/cit25","doi-asserted-by":"publisher","DOI":"10.1016\/S0014-5793(03)01275-4"},{"key":"ref26\/cit26","unstructured":"Qian, C.; Tang, H.; Yang, Z.; Liang, H.; Liu, Y. Can large language models empower molecular property prediction? 2023, arXiv:2307.07443. arXiv.org e-Printarchive https:\/\/arxiv.org\/abs\/2307.07443."},{"key":"ref27\/cit27","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.106177"},{"key":"ref28\/cit28","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-018-0279-6"},{"key":"ref29\/cit29","doi-asserted-by":"publisher","DOI":"10.1021\/ci00005a010"},{"issue":"1","key":"ref30\/cit30","first-page":"153","volume":"145","author":"Riba A.","year":"2011","journal-title":"Cell"},{"key":"ref31\/cit31","doi-asserted-by":"publisher","DOI":"10.1021\/ci100050t"},{"key":"ref32\/cit32","unstructured":"Rong, Y.; Bian, Y.; Xu, T.; Xie, W.; Wei, W.; Huang, J.; Huang, L. In\n                      Self-Supervised Graph Transformer on Large-Scale Molecular Data\n                      , Advances in Neural Information Processing Systems; NIPS, 2020."},{"key":"ref33\/cit33","doi-asserted-by":"publisher","DOI":"10.1021\/ci300415d"},{"key":"ref34\/cit34","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2020.105807"},{"key":"ref35\/cit35","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-09885-4"},{"issue":"2","key":"ref36\/cit36","first-page":"500","volume":"63","author":"Shi X.","year":"2023","journal-title":"J. Chem. Inf. Model."},{"key":"ref37\/cit37","volume-title":"Molecular Descriptors for Chemoinformatics: Volume I: Alphabetical Listing\/Volume II: Appendices, References","author":"Todeschini R.","year":"2009"},{"key":"ref38\/cit38","doi-asserted-by":"publisher","DOI":"10.1021\/ci200409x"},{"key":"ref39\/cit39","doi-asserted-by":"crossref","unstructured":"Wang, S.; Guo, Y.; Wang, Y.; Sun, H.; Huang, J. In\n                      Smiles-Bert: Large Scale Unsupervised Pre-Training for Molecular Property Prediction In\n                      , Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics; Association for Computing Machinery: New York, NY, USA, 2019; pp 429\u2013436.","DOI":"10.1145\/3307339.3342186"},{"issue":"10","key":"ref40\/cit40","first-page":"7894","volume":"123","author":"Xu L.","year":"2023","journal-title":"Chem. Rev."},{"issue":"3","key":"ref41\/cit41","doi-asserted-by":"crossref","first-page":"abc123","DOI":"10.1093\/bioinformatics\/btae123","volume":"40","author":"Yang H.","year":"2024","journal-title":"Bioinformatics"},{"key":"ref42\/cit42","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/17.suppl_1.S316"},{"key":"ref43\/cit43","doi-asserted-by":"crossref","unstructured":"Zhang, L.; Wang, X.; Li, H.; Zhu, G.; Shen, P.; Li, P.; Lu, X.; Ali Shah, S. A.; Bennamoun, M. In\n                      Structure-Feature Based Graph Self-Adaptive Pooling\n                      , Proceedings of The Web Conference 2020; Association for Computing Machinery: New York, NY, USA, 2020; pp 3098\u20133104.","DOI":"10.1145\/3366423.3380083"},{"key":"ref44\/cit44","unstructured":"Muhan, Z.; Chen, Y.\n                      Neural Networks: Foundations, Frontiers, and Applications\n                      ; Springer, 2022; pp 195\u2013223."},{"issue":"14","key":"ref45\/cit45","first-page":"7498","volume":"63","author":"Zhou Z.","year":"2020","journal-title":"J. Med. Chem."}],"container-title":["Journal of Chemical Information and Modeling"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.jcim.5c00950","content-type":"application\/pdf","content-version":"vor","intended-application":"unspecified"},{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.jcim.5c00950","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,10]],"date-time":"2025-11-10T09:12:04Z","timestamp":1762765924000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/doi\/10.1021\/acs.jcim.5c00950"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"references-count":45,"journal-issue":{"issue":"21","published-print":{"date-parts":[[2025,11,10]]}},"alternative-id":["10.1021\/acs.jcim.5c00950"],"URL":"https:\/\/doi.org\/10.1021\/acs.jcim.5c00950","relation":{},"ISSN":["1549-9596","1549-960X"],"issn-type":[{"value":"1549-9596","type":"print"},{"value":"1549-960X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}