{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T13:46:42Z","timestamp":1743083202389,"version":"3.40.3"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031105616"},{"type":"electronic","value":"9783031105623"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-10562-3_10","type":"book-chapter","created":{"date-parts":[[2022,8,3]],"date-time":"2022-08-03T14:25:15Z","timestamp":1659536715000},"page":"127-139","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Virtual Screening Based on Electrostatic Similarity and Flexible Ligands"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8956-1733","authenticated-orcid":false,"given":"Sav\u00edns","family":"Puertas-Mart\u00edn","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2826-1635","authenticated-orcid":false,"given":"Juana L.","family":"Redondo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1158-8877","authenticated-orcid":false,"given":"Antonio J.","family":"Banegas-Luna","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0568-5470","authenticated-orcid":false,"given":"Ester M.","family":"Garz\u00f3n","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4468-7898","authenticated-orcid":false,"given":"Horacio","family":"P\u00e9rez-S\u00e1nchez","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8403-3111","authenticated-orcid":false,"given":"Valerie J.","family":"Gillet","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6514-6543","authenticated-orcid":false,"given":"Pilar M.","family":"Ortigosa","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,8,4]]},"reference":[{"issue":"5","key":"10_CR1","doi-asserted-by":"publisher","first-page":"954","DOI":"10.1109\/TCBB.2015.2498553","volume":"13","author":"A Axenopoulos","year":"2016","unstructured":"Axenopoulos, A., Rafailidis, D., Papadopoulos, G., Houstis, E.N., Daras, P.: Similarity search of flexible 3D molecules combining local and global shape descriptors. IEEE\/ACM Trans. Comput. Biol. Bioinf. 13(5), 954\u2013970 (2016). https:\/\/doi.org\/10.1109\/TCBB.2015.2498553","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinf."},{"key":"10_CR2","doi-asserted-by":"publisher","unstructured":"Bahi, M., Batouche, M.: Deep learning for ligand-based virtual screening in drug discovery. In: 2018 3rd International Conference on Pattern Analysis and Intelligent Systems (PAIS), pp. 1\u20135 (2018). https:\/\/doi.org\/10.1109\/PAIS.2018.8598488","DOI":"10.1109\/PAIS.2018.8598488"},{"key":"10_CR3","doi-asserted-by":"publisher","unstructured":"B\u00f6ttcher, C., Belle, O.V., Belle, B.: Theory of Electric Polarization. Elsevier, Amsterdam (1974). https:\/\/doi.org\/10.1016\/B978-0-444-41019-1.50006-7","DOI":"10.1016\/B978-0-444-41019-1.50006-7"},{"key":"10_CR4","doi-asserted-by":"publisher","unstructured":"Fatumo, S., Adebiyi, M., Adebiyi, E.: In silico models for drug resistance. In: Kortagere, S. (eds.) In Silico Models for Drug Discovery. Methods in Molecular Biology, vol. 993. Humana Press, Totowa (2013). https:\/\/doi.org\/10.1007\/978-1-62703-342-8_4","DOI":"10.1007\/978-1-62703-342-8_4"},{"key":"10_CR5","doi-asserted-by":"publisher","unstructured":"Hu, J., Liu, Z., Yu, D.J., Zhang, Y.: LS-align: an atom-level, flexible ligand structural alignment algorithm for high-throughput virtual screening. In: Bioinformatics, vol. 34, pp. 2209\u20132218. Oxford University Press (2018). https:\/\/doi.org\/10.1093\/bioinformatics\/bty081","DOI":"10.1093\/bioinformatics\/bty081"},{"key":"10_CR6","first-page":"241","volume":"37","author":"P Jaccard","year":"1901","unstructured":"Jaccard, P.: Distribution de la flore alpine dans le bassin des dranses et dans quelques r\u00e9gions voisines. Bulletin de la Soci\u00e9t\u00e9 Vaudoise des Sciences Naturelles 37, 241\u2013272 (1901)","journal-title":"Bulletin de la Soci\u00e9t\u00e9 Vaudoise des Sciences Naturelles"},{"key":"10_CR7","doi-asserted-by":"publisher","unstructured":"Kal\u00e1szi, A., Szisz, D., Imre, G., Polg\u00e1r, T.: Screen3D: a novel fully flexible high-throughput shape-similarity search method. J. Chem. Inf. Model. 54(4), 1036\u20131049 (2014). https:\/\/doi.org\/10.1021\/ci400620f","DOI":"10.1021\/ci400620f"},{"key":"10_CR8","unstructured":"OMEGA 4.1.0.2: OpenEye Scientific Software: Santa Fe, NM, USA (2019). http:\/\/www.eyesopen.com"},{"issue":"1","key":"10_CR9","doi-asserted-by":"publisher","first-page":"1398","DOI":"10.1038\/s41598-018-37908-6","volume":"9","author":"S Puertas-Mart\u00edn","year":"2019","unstructured":"Puertas-Mart\u00edn, S., Redondo, J.L., Ortigosa, P.M., P\u00e9rez-S\u00e1nchez, H.: OptiPharm: an evolutionary algorithm to compare shape similarity. Sci. Rep. 9(1), 1398 (2019). https:\/\/doi.org\/10.1038\/s41598-018-37908-6","journal-title":"Sci. Rep."},{"key":"10_CR10","doi-asserted-by":"publisher","unstructured":"Puertas-Mart\u00edn, S., Redondo, J.L., P\u00e9rez-S\u00e1nchez, H., Ortigosa, P.M.: Optimizing electrostatic similarity for virtual screening: a new methodology. In: Informatica, pp. 1\u201319 (2020). https:\/\/doi.org\/10.15388\/20-INFOR424","DOI":"10.15388\/20-INFOR424"},{"key":"10_CR11","unstructured":"ROCS: OpenEye Scientific Software: Santa Fe, NM. http:\/\/www.eyesopen.com"},{"issue":"7\u20138","key":"10_CR12","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1016\/j.drudis.2013.01.007","volume":"18","author":"Y Tanrikulu","year":"2013","unstructured":"Tanrikulu, Y., Kr\u00fcger, B., Proschak, E.: The holistic integration of virtual screening in drug discovery. Drug Discov. Today 18(7\u20138), 358\u2013364 (2013). https:\/\/doi.org\/10.1016\/j.drudis.2013.01.007","journal-title":"Drug Discov. Today"},{"key":"10_CR13","unstructured":"VIDA 4.4.0.4: OpenEye Scientific Software: Santa Fe, NM. http:\/\/www.eyesopen.com"},{"key":"10_CR14","doi-asserted-by":"publisher","unstructured":"V\u00e1zquez, J., L\u00f3pez, M., Gibert, E., Herrero, E., Luque, F.J.: Merging ligand-based and structure-based methods in drug discovery: an overview of combined virtual screening approaches. Molecules 25(20), 4723 (2020). https:\/\/doi.org\/10.3390\/molecules25204723","DOI":"10.3390\/molecules25204723"},{"key":"10_CR15","doi-asserted-by":"publisher","unstructured":"Wishart, D.S., et al.: DrugBank 5.0: a major update to the DrugBank database for 2018. Nucl. Acids Res. 46(D1), D1074\u2013D1082 (2018). https:\/\/doi.org\/10.1093\/nar\/gkx1037","DOI":"10.1093\/nar\/gkx1037"},{"issue":"2","key":"10_CR16","doi-asserted-by":"publisher","first-page":"1053","DOI":"10.1093\/bib\/bbaa422","volume":"22","author":"Y Yang","year":"2021","unstructured":"Yang, Y., et al.: Ligand-based approach for predicting drug targets and for virtual screening against COVID-19. Brief. Bioinform. 22(2), 1053\u20131064 (2021). https:\/\/doi.org\/10.1093\/bib\/bbaa422","journal-title":"Brief. Bioinform."}],"container-title":["Lecture Notes in Computer Science","Computational Science and Its Applications \u2013 ICCSA 2022 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-10562-3_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,3]],"date-time":"2022-08-03T14:27:22Z","timestamp":1659536842000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-10562-3_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031105616","9783031105623"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-10562-3_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"4 August 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCSA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Science and Its Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Malaga","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 July 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 July 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccsa2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iccsa.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CyberChair 4","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"279","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"57","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"20% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.6","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"8.7","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"285 Workshop submission accepted out of 815 submissions","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}