{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,12]],"date-time":"2025-05-12T08:40:04Z","timestamp":1747039204756,"version":"3.40.5"},"reference-count":44,"publisher":"American Chemical Society (ACS)","issue":"9","license":[{"start":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T00:00:00Z","timestamp":1745798400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001870","name":"Fundacja na rzecz Nauki Polskiej","doi-asserted-by":"publisher","award":["FIRST TEAM FENG.02.02-IP.05-0039\/23"],"award-info":[{"award-number":["FIRST TEAM FENG.02.02-IP.05-0039\/23"]}],"id":[{"id":"10.13039\/501100001870","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Chem. Inf. Model."],"published-print":{"date-parts":[[2025,5,12]]},"DOI":"10.1021\/acs.jcim.5c00698","type":"journal-article","created":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T11:29:03Z","timestamp":1745839743000},"page":"4412-4425","source":"Crossref","is-referenced-by-count":0,"title":["PROFIS: Design of Target-Focused Libraries by Probing Continuous Fingerprint Space with Recurrent Neural Networks"],"prefix":"10.1021","volume":"65","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-1461-1346","authenticated-orcid":true,"given":"Hubert","family":"Rybka","sequence":"first","affiliation":[{"name":"Doctoral School of Exact and Natural Sciences, Jagiellonian University, \u0141ojasiewicza 11, 30-348 Krak\u00f3w, Poland"},{"name":"Faculty of Chemistry, Jagiellonian University, Gronostajowa 2, 30-387 Krak\u00f3w, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6053-0028","authenticated-orcid":true,"given":"Tomasz","family":"Danel","sequence":"additional","affiliation":[{"name":"Faculty of Chemistry, Jagiellonian University, Gronostajowa 2, 30-387 Krak\u00f3w, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2891-5603","authenticated-orcid":true,"given":"Sabina","family":"Podlewska","sequence":"additional","affiliation":[{"name":"Maj Institute of Pharmacology, Polish Academy of Sciences, Sm\u0229tna 12, 31-343 Krak\u00f3w, Poland"}]}],"member":"316","published-online":{"date-parts":[[2025,4,28]]},"reference":[{"key":"ref1\/cit1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2020.1166"},{"key":"ref2\/cit2","doi-asserted-by":"publisher","DOI":"10.1124\/pr.112.007336"},{"key":"ref3\/cit3","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-05905-z"},{"key":"ref4\/cit4","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-021-10058-4"},{"key":"ref5\/cit5","doi-asserted-by":"publisher","DOI":"10.1002\/wcms.1568"},{"key":"ref6\/cit6","doi-asserted-by":"publisher","DOI":"10.1021\/ci00057a005"},{"key":"ref7\/cit7","doi-asserted-by":"crossref","unstructured":"O\u2019Boyle, N.; Dalke, A. DeepSMILES: an adaptation of SMILES for use in machine-learning of chemical structures ChemRxiv 2018.","DOI":"10.26434\/chemrxiv.7097960.v1"},{"key":"ref8\/cit8","doi-asserted-by":"publisher","DOI":"10.1088\/2632-2153\/aba947"},{"key":"ref9\/cit9","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1186\/1758-2946-4-22","volume":"4","author":"O\u2019Boyle N. M.","year":"2012","journal-title":"J. Cheminf."},{"key":"ref10\/cit10","doi-asserted-by":"publisher","DOI":"10.1021\/ci100050t"},{"key":"ref11\/cit11","doi-asserted-by":"publisher","DOI":"10.1021\/ci010132r"},{"key":"ref12\/cit12","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btn479"},{"key":"ref13\/cit13","doi-asserted-by":"publisher","DOI":"10.3390\/ddc2020017"},{"key":"ref14\/cit14","doi-asserted-by":"publisher","DOI":"10.2174\/09298673113209990001"},{"key":"ref15\/cit15","unstructured":"Kingma, D. P.; Welling, M. Auto-encoding variational bayes, arXiv:1312.6114. arXiv.org e-Print archive, 2013. https:\/\/arxiv.org\/abs\/1312.6114."},{"key":"ref16\/cit16","doi-asserted-by":"publisher","DOI":"10.1021\/acscentsci.7b00572"},{"key":"ref17\/cit17","first-page":"2323","author":"Jin W.","year":"2018","journal-title":"Int. Conf. Mach. Learn."},{"key":"ref18\/cit18","doi-asserted-by":"crossref","unstructured":"Alperstein, Z.; Cherkasov, A.; Rolfe, J. T. QSPR\/QSAR Analysis Using SMILES and Quasi-SMILES; Springer, 2023; pp 85\u2013115.","DOI":"10.1007\/978-3-031-28401-4_4"},{"key":"ref19\/cit19","doi-asserted-by":"crossref","unstructured":"Kai, L.; Wei, Z.; Ming, G. In  Molecular Design Method based on New Molecular Representation and Variational Auto-Encoder, CS & IT Conference Proceedings; Open Access Conference Proceedings, 2023.","DOI":"10.5121\/csit.2023.130303"},{"key":"ref20\/cit20","doi-asserted-by":"publisher","DOI":"10.3390\/ph14080758"},{"key":"ref21\/cit21","doi-asserted-by":"publisher","DOI":"10.1021\/ci700107y"},{"key":"ref22\/cit22","doi-asserted-by":"publisher","DOI":"10.1021\/mp300237z"},{"key":"ref23\/cit23","doi-asserted-by":"publisher","DOI":"10.1039\/D0SC03115A"},{"key":"ref24\/cit24","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1186\/s13321-023-00693-0","volume":"15","author":"Ucak U. V.","year":"2023","journal-title":"J. Cheminf."},{"key":"ref25\/cit25","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-020-0174-5"},{"key":"ref26\/cit26","doi-asserted-by":"crossref","unstructured":"Cho, K.; Van Merri\u00ebnboer, B.; Bahdanau, D.; Bengio, Y. On the properties of neural machine translation: Encoder-decoder approaches, arXiv:1409.1259. arXiv.org e-Print archive, 2014. https:\/\/arxiv.org\/abs\/1409.1259.","DOI":"10.3115\/v1\/W14-4012"},{"key":"ref27\/cit27","doi-asserted-by":"crossref","unstructured":"Yang, S.; Yu, X.; Zhou, Y. In  LSTM and GRU Neural Network Performance Comparison Study: Taking Yelp Review Dataset as an Example, 2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI); IEEE, 2020.","DOI":"10.1109\/IWECAI50956.2020.00027"},{"key":"ref28\/cit28","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gky1075"},{"key":"ref29\/cit29","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.0c00675"},{"key":"ref30\/cit30","unstructured":"RDKit: Open-Source Cheminformatics. http:\/\/www.rdkit.org."},{"key":"ref31\/cit31","doi-asserted-by":"publisher","DOI":"10.1021\/jm9602928"},{"key":"ref32\/cit32","doi-asserted-by":"crossref","unstructured":"Fu, H.; Li, C.; Liu, X.; Gao, J.; Celikyilmaz, A.; Carin, L. Cyclical annealing schedule: A simple approach to mitigating kl vanishing, arXiv.org e-Print archive. https:\/\/arxiv.org\/abs\/1903.10145, 2019. https:\/\/arxiv.org\/abs\/1903.10145.","DOI":"10.18653\/v1\/N19-1021"},{"key":"ref33\/cit33","first-page":"2825","volume":"12","author":"Pedregosa F.","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref34\/cit34","doi-asserted-by":"crossref","unstructured":"Chen, T.; Guestrin, C. In  Xgboost: A Scalable Tree Boosting System, Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; ACM, 2016; pp 785\u2013794.","DOI":"10.1145\/2939672.2939785"},{"key":"ref35\/cit35","unstructured":"Nogueira, F. Bayesian Optimization: Open Source Constrained Global Optimization Tool for Python. https:\/\/github.com\/fmfn\/BayesianOptimization."},{"key":"ref36\/cit36","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-14884-y"},{"key":"ref37\/cit37","doi-asserted-by":"publisher","DOI":"10.1074\/jbc.RA119.011809"},{"key":"ref38\/cit38","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.7b00190"},{"key":"ref39\/cit39","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-021-00522-2"},{"key":"ref40\/cit40","doi-asserted-by":"publisher","DOI":"10.1038\/nchem.1243"},{"key":"ref41\/cit41","doi-asserted-by":"publisher","DOI":"10.1016\/j.ddtec.2004.10.009"},{"key":"ref42\/cit42","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemolab.2015.04.013"},{"key":"ref43\/cit43","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-017-0230-2"},{"key":"ref44\/cit44","doi-asserted-by":"publisher","DOI":"10.1021\/ci100253r"}],"container-title":["Journal of Chemical Information and Modeling"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.jcim.5c00698","content-type":"application\/pdf","content-version":"vor","intended-application":"unspecified"},{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.jcim.5c00698","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,12]],"date-time":"2025-05-12T08:10:43Z","timestamp":1747037443000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/doi\/10.1021\/acs.jcim.5c00698"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,28]]},"references-count":44,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2025,5,12]]}},"alternative-id":["10.1021\/acs.jcim.5c00698"],"URL":"https:\/\/doi.org\/10.1021\/acs.jcim.5c00698","relation":{},"ISSN":["1549-9596","1549-960X"],"issn-type":[{"type":"print","value":"1549-9596"},{"type":"electronic","value":"1549-960X"}],"subject":[],"published":{"date-parts":[[2025,4,28]]}}}