{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T04:27:29Z","timestamp":1743049649945,"version":"3.40.3"},"publisher-location":"Cham","reference-count":38,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031781971"},{"type":"electronic","value":"9783031781988"}],"license":[{"start":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T00:00:00Z","timestamp":1733270400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T00:00:00Z","timestamp":1733270400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-78198-8_14","type":"book-chapter","created":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T09:04:41Z","timestamp":1733216681000},"page":"203-219","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["DRIVPocket: A Dual-stream Rotation Invariance in Feature Sampling and Voxel Fusion Approach for Protein Binding Site Prediction"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-8397-3952","authenticated-orcid":false,"given":"Bowen","family":"Deng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1485-4632","authenticated-orcid":false,"given":"Yang","family":"Hua","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenjie","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoning","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao-jun","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,4]]},"reference":[{"issue":"21","key":"14_CR1","doi-asserted-by":"publisher","first-page":"5069","DOI":"10.1021\/acs.jcim.1c00799","volume":"62","author":"R Aggarwal","year":"2021","unstructured":"Aggarwal, R., Gupta, A., Chelur, V., Jawahar, C., Priyakumar, U.D.: Deeppocket: ligand binding site detection and segmentation using 3d convolutional neural networks. J. Chem. Inf. Model. 62(21), 5069\u20135079 (2021)","journal-title":"J. Chem. Inf. Model."},{"issue":"9","key":"14_CR2","doi-asserted-by":"publisher","first-page":"787","DOI":"10.1016\/j.chembiol.2003.09.002","volume":"10","author":"AC Anderson","year":"2003","unstructured":"Anderson, A.C.: The process of structure-based drug design. Chemistry & biology 10(9), 787\u2013797 (2003)","journal-title":"Chemistry & biology"},{"issue":"1","key":"14_CR3","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1073\/pnas.0707684105","volume":"105","author":"M Brylinski","year":"2008","unstructured":"Brylinski, M., Skolnick, J.: A threading-based method (findsite) for ligand-binding site prediction and functional annotation. Proc. Natl. Acad. Sci. 105(1), 129\u2013134 (2008)","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"5","key":"14_CR4","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1016\/j.str.2011.02.015","volume":"19","author":"K Chen","year":"2011","unstructured":"Chen, K., Mizianty, M.J., Gao, J., Kurgan, L.: A critical comparative assessment of predictions of protein-binding sites for biologically relevant organic compounds. Structure 19(5), 613\u2013621 (2011)","journal-title":"Structure"},{"issue":"D1","key":"14_CR5","doi-asserted-by":"publisher","first-page":"D399","DOI":"10.1093\/nar\/gku928","volume":"43","author":"J Desaphy","year":"2015","unstructured":"Desaphy, J., Bret, G., Rognan, D., Kellenberger, E.: sc-pdb: a 3d-database of ligandable binding sites-10 years on. Nucleic Acids Res. 43(D1), D399\u2013D404 (2015)","journal-title":"Nucleic Acids Res."},{"issue":"6","key":"14_CR6","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1016\/S1093-3263(98)00002-3","volume":"15","author":"M Hendlich","year":"1997","unstructured":"Hendlich, M., Rippmann, F., Barnickel, G.: Ligsite: automatic and efficient detection of potential small molecule-binding sites in proteins. J. Mol. Graph. Model. 15(6), 359\u2013363 (1997)","journal-title":"J. Mol. Graph. Model."},{"issue":"1","key":"14_CR7","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1109\/TCBB.2022.3144008","volume":"20","author":"Y Hua","year":"2022","unstructured":"Hua, Y., Song, X., Feng, Z., Wu, X.J., Kittler, J., Yu, D.J.: Cpinformer for efficient and robust compound-protein interaction prediction. IEEE\/ACM Trans. Comput. Biol. Bioinf. 20(1), 285\u2013296 (2022)","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinf."},{"key":"14_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1472-6807-6-19","volume":"6","author":"B Huang","year":"2006","unstructured":"Huang, B., Schroeder, M.: Ligsite csc: predicting ligand binding sites using the connolly surface and degree of conservation. BMC Struct. Biol. 6, 1\u201311 (2006)","journal-title":"BMC Struct. Biol."},{"issue":"19","key":"14_CR9","doi-asserted-by":"publisher","first-page":"3036","DOI":"10.1093\/bioinformatics\/btx350","volume":"33","author":"J Jim\u00e9nez","year":"2017","unstructured":"Jim\u00e9nez, J., Doerr, S., Mart\u00ednez-Rosell, G., Rose, A.S., De Fabritiis, G.: Deepsite: protein-binding site predictor using 3d-convolutional neural networks. Bioinformatics 33(19), 3036\u20133042 (2017)","journal-title":"Bioinformatics"},{"key":"14_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13321-021-00547-7","volume":"13","author":"J Kandel","year":"2021","unstructured":"Kandel, J., Tayara, H., Chong, K.T.: Puresnet: prediction of protein-ligand binding sites using deep residual neural network. Journal of cheminformatics 13, 1\u201314 (2021)","journal-title":"Journal of cheminformatics"},{"issue":"5","key":"14_CR11","doi-asserted-by":"publisher","first-page":"733","DOI":"10.1038\/nprot.2015.043","volume":"10","author":"D Kozakov","year":"2015","unstructured":"Kozakov, D., Grove, L.E., Hall, D.R., Bohnuud, T., Mottarella, S.E., Luo, L., Xia, B., Beglov, D., Vajda, S.: The ftmap family of web servers for determining and characterizing ligand-binding hot spots of proteins. Nat. Protoc. 10(5), 733\u2013755 (2015)","journal-title":"Nat. Protoc."},{"key":"14_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13321-015-0059-5","volume":"7","author":"R Kriv\u00e1k","year":"2015","unstructured":"Kriv\u00e1k, R., Hoksza, D.: Improving protein-ligand binding site prediction accuracy by classification of inner pocket points using local features. Journal of cheminformatics 7, 1\u201313 (2015)","journal-title":"Journal of cheminformatics"},{"key":"14_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13321-018-0285-8","volume":"10","author":"R Kriv\u00e1k","year":"2018","unstructured":"Kriv\u00e1k, R., Hoksza, D.: P2rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure. Journal of cheminformatics 10, 1\u201312 (2018)","journal-title":"Journal of cheminformatics"},{"issue":"9","key":"14_CR14","doi-asserted-by":"publisher","first-page":"1908","DOI":"10.1093\/bioinformatics\/bti315","volume":"21","author":"AT Laurie","year":"2005","unstructured":"Laurie, A.T., Jackson, R.M.: Q-sitefinder: an energy-based method for the prediction of protein-ligand binding sites. Bioinformatics 21(9), 1908\u20131916 (2005)","journal-title":"Bioinformatics"},{"key":"14_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-2105-10-168","volume":"10","author":"V Le Guilloux","year":"2009","unstructured":"Le Guilloux, V., Schmidtke, P., Tuffery, P.: Fpocket: an open source platform for ligand pocket detection. BMC Bioinformatics 10, 1\u201311 (2009)","journal-title":"BMC Bioinformatics"},{"key":"14_CR16","doi-asserted-by":"crossref","unstructured":"Li, P., Cao, B., Tu, S., Xu, L.: Recurpocket: Recurrent lmser network with gating mechanism for protein binding site detection. In: 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). pp. 334\u2013339. IEEE (2022)","DOI":"10.1109\/BIBM55620.2022.9995656"},{"key":"14_CR17","doi-asserted-by":"crossref","unstructured":"Li, P., Liu, Y., Tu, S., Xu, L.: Glpocket: A multi-scale representation learning approach for protein binding site prediction. In: Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI-23. vol.\u00a08, pp. 4821\u20134828 (2023)","DOI":"10.24963\/ijcai.2023\/536"},{"key":"14_CR18","doi-asserted-by":"crossref","unstructured":"Liu, Y., Grimm, M., Dai, W.t., Hou, M.c., Xiao, Z.X., Cao, Y.: Cb-dock: A web server for cavity detection-guided protein\u2013ligand blind docking. Acta Pharmacologica Sinica 41(1), 138\u2013144 (2020)","DOI":"10.1038\/s41401-019-0228-6"},{"key":"14_CR19","doi-asserted-by":"crossref","unstructured":"Liu, Y., Li, P., Tu, S., Xu, L.: Refinepocket: An attention-enhanced and mask-guided deep learning approach for protein binding site prediction. IEEE\/ACM Transactions on Computational Biology and Bioinformatics (2023)","DOI":"10.1109\/TCBB.2023.3265640"},{"key":"14_CR20","doi-asserted-by":"crossref","unstructured":"Lu, C., Mitra, K., Mitra, K., Meng, H., Rich-New, S.T., Wang, F., Si, D.: Protein-ligand binding site prediction and de novo ligand generation from cryo-em maps. bioRxiv pp. 2023\u201311 (2023)","DOI":"10.1101\/2023.11.16.567458"},{"key":"14_CR21","doi-asserted-by":"publisher","first-page":"1686","DOI":"10.1007\/s12272-015-0640-5","volume":"38","author":"SJY Macalino","year":"2015","unstructured":"Macalino, S.J.Y., Gosu, V., Hong, S., Choi, S.: Role of computer-aided drug design in modern drug discovery. Arch. Pharmacal Res. 38, 1686\u20131701 (2015)","journal-title":"Arch. Pharmacal Res."},{"issue":"12","key":"14_CR22","doi-asserted-by":"publisher","first-page":"1681","DOI":"10.1093\/bioinformatics\/btab009","volume":"37","author":"SK Mylonas","year":"2021","unstructured":"Mylonas, S.K., Axenopoulos, A., Daras, P.: Deepsurf: a surface-based deep learning approach for the prediction of ligand binding sites on proteins. Bioinformatics 37(12), 1681\u20131690 (2021)","journal-title":"Bioinformatics"},{"issue":"02","key":"14_CR23","doi-asserted-by":"publisher","first-page":"2150006","DOI":"10.1142\/S0219720021500062","volume":"19","author":"F Nazem","year":"2021","unstructured":"Nazem, F., Ghasemi, F., Fassihi, A., Dehnavi, A.M.: 3d u-net: A voxel-based method in binding site prediction of protein structure. J. Bioinform. Comput. Biol. 19(02), 2150006 (2021)","journal-title":"J. Bioinform. Comput. Biol."},{"issue":"2","key":"14_CR24","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1093\/bioinformatics\/btr651","volume":"28","author":"CH Ngan","year":"2012","unstructured":"Ngan, C.H., Hall, D.R., Zerbe, B., Grove, L.E., Kozakov, D., Vajda, S.: Ftsite: high accuracy detection of ligand binding sites on unbound protein structures. Bioinformatics 28(2), 286\u2013287 (2012)","journal-title":"Bioinformatics"},{"key":"14_CR25","unstructured":"Qi, C.R., Su, H., Mo, K., Guibas, L.J.: Pointnet: Deep learning on point sets for 3d classification and segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 652\u2013660 (2017)"},{"issue":"20","key":"14_CR26","doi-asserted-by":"publisher","first-page":"3142","DOI":"10.1093\/bioinformatics\/btw367","volume":"32","author":"PA Ravindranath","year":"2016","unstructured":"Ravindranath, P.A., Sanner, M.F.: Autosite: an automated approach for pseudo-ligands prediction-from ligand-binding sites identification to predicting key ligand atoms. Bioinformatics 32(20), 3142\u20133149 (2016)","journal-title":"Bioinformatics"},{"key":"14_CR27","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: Convolutional networks for biomedical image segmentation. In: Medical image computing and computer-assisted intervention\u2013MICCAI 2015: 18th international conference, Munich, Germany, October 5-9, 2015, proceedings, part III 18. pp. 234\u2013241. Springer (2015)","DOI":"10.1007\/978-3-319-24574-4_28"},{"issue":"1","key":"14_CR28","doi-asserted-by":"publisher","first-page":"5035","DOI":"10.1038\/s41598-020-61860-z","volume":"10","author":"MM Stepniewska-Dziubinska","year":"2020","unstructured":"Stepniewska-Dziubinska, M.M., Zielenkiewicz, P., Siedlecki, P.: Improving detection of protein-ligand binding sites with 3d segmentation. Sci. Rep. 10(1), 5035 (2020)","journal-title":"Sci. Rep."},{"issue":"3","key":"14_CR29","doi-asserted-by":"publisher","first-page":"1079","DOI":"10.1021\/acs.jcim.9b01145","volume":"60","author":"J Sunseri","year":"2020","unstructured":"Sunseri, J., Koes, D.R.: Libmolgrid: graphics processing unit accelerated molecular gridding for deep learning applications. J. Chem. Inf. Model. 60(3), 1079\u20131084 (2020)","journal-title":"J. Chem. Inf. Model."},{"issue":"13","key":"14_CR30","doi-asserted-by":"publisher","first-page":"5313","DOI":"10.1073\/pnas.1102210108","volume":"108","author":"YY Tseng","year":"2011","unstructured":"Tseng, Y.Y., Li, W.H.: Evolutionary approach to predicting the binding site residues of a protein from its primary sequence. Proc. Natl. Acad. Sci. 108(13), 5313\u20135318 (2011)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"14_CR31","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., Polosukhin, I.: Attention is all you need. Advances in neural information processing systems 30 (2017)"},{"issue":"12","key":"14_CR32","doi-asserted-by":"publisher","first-page":"4111","DOI":"10.1021\/jm048957q","volume":"48","author":"R Wang","year":"2005","unstructured":"Wang, R., Fang, X., Lu, Y., Yang, C.Y., Wang, S.: The pdbbind database: methodologies and updates. J. Med. Chem. 48(12), 4111\u20134119 (2005)","journal-title":"J. Med. Chem."},{"key":"14_CR33","doi-asserted-by":"crossref","unstructured":"Wang, X., Zhao, B., Yang, P., Tan, Y., Ma, R., Rao, S., Du, J., Chen, J., Zhou, J., Liu, S.: Dunet: A deep learning guided protein-ligand binding pocket prediction. bioRxiv pp. 2022\u201308 (2022)","DOI":"10.1101\/2022.08.11.503579"},{"key":"14_CR34","doi-asserted-by":"crossref","unstructured":"Wass, M.N., Kelley, L.A., Sternberg, M.J.: 3dligandsite: predicting ligand-binding sites using similar structures. Nucleic acids research 38(suppl_2), W469\u2013W473 (2010)","DOI":"10.1093\/nar\/gkq406"},{"key":"14_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1752-153X-1-7","volume":"1","author":"M Weisel","year":"2007","unstructured":"Weisel, M., Proschak, E., Schneider, G.: Pocketpicker: analysis of ligand binding-sites with shape descriptors. Chem. Cent. J. 1, 1\u201317 (2007)","journal-title":"Chem. Cent. J."},{"issue":"11","key":"14_CR36","doi-asserted-by":"publisher","first-page":"2835","DOI":"10.1021\/acs.jcim.1c01512","volume":"62","author":"X Yan","year":"2022","unstructured":"Yan, X., Lu, Y., Li, Z., Wei, Q., Gao, X., Wang, S., Wu, S., Cui, S.: Pointsite: a point cloud segmentation tool for identification of protein ligand binding atoms. J. Chem. Inf. Model. 62(11), 2835\u20132845 (2022)","journal-title":"J. Chem. Inf. Model."},{"issue":"5","key":"14_CR37","doi-asserted-by":"publisher","first-page":"1228","DOI":"10.1007\/s11263-022-01601-z","volume":"130","author":"Z Zhang","year":"2022","unstructured":"Zhang, Z., Hua, B.S., Yeung, S.K.: Riconv++: Effective rotation invariant convolutions for 3d point clouds deep learning. Int. J. Comput. Vision 130(5), 1228\u20131243 (2022)","journal-title":"Int. J. Comput. Vision"},{"key":"14_CR38","doi-asserted-by":"crossref","unstructured":"Zhou, H., Zhang, S., Peng, J., Zhang, S., Li, J., Xiong, H., Zhang, W.: Informer: Beyond efficient transformer for long sequence time-series forecasting. In: Proceedings of the AAAI conference on artificial intelligence. vol.\u00a035, pp. 11106\u201311115 (2021)","DOI":"10.1609\/aaai.v35i12.17325"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-78198-8_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T10:19:55Z","timestamp":1733221195000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-78198-8_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,4]]},"ISBN":["9783031781971","9783031781988"],"references-count":38,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-78198-8_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,12,4]]},"assertion":[{"value":"4 December 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kolkata","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpr2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icpr2024.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}