{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T11:07:58Z","timestamp":1779448078408,"version":"3.53.1"},"reference-count":43,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62166001"],"award-info":[{"award-number":["62166001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computational Biology and Chemistry"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1016\/j.compbiolchem.2025.108559","type":"journal-article","created":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T11:52:04Z","timestamp":1751025124000},"page":"108559","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["A systematic framework enhancing molecular screening efficiency in drug discovery via scaffold-driven fuzzy similarity and adaptive spectral clustering"],"prefix":"10.1016","volume":"119","author":[{"given":"Zeqiang","family":"Xian","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caihui","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.compbiolchem.2025.108559_b1","first-page":"1","article-title":"A bibliometric analysis of the cheminformatics\/QSAR literature (2000\u20132023) for predictive modeling in data science using the SCOPUS database","author":"Banerjee","year":"2024","journal-title":"Mol. Divers."},{"key":"10.1016\/j.compbiolchem.2025.108559_b2","series-title":"International Conference on Data Science and Applications","first-page":"515","article-title":"Enhancing the performance of PSO algorithm for clustering high-dimensional data using autoencoders","author":"Battur","year":"2023"},{"issue":"4","key":"10.1016\/j.compbiolchem.2025.108559_b3","doi-asserted-by":"crossref","first-page":"1040","DOI":"10.1016\/j.drudis.2020.11.037","article-title":"Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 2: a discussion of chemical and biological data","volume":"26","author":"Bender","year":"2021","journal-title":"Drug Discov. Today"},{"issue":"2\u20133","key":"10.1016\/j.compbiolchem.2025.108559_b4","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/0098-3004(84)90020-7","article-title":"FCM: The fuzzy c-means clustering algorithm","volume":"10","author":"Bezdek","year":"1984","journal-title":"Comput. Geosci."},{"issue":"3\u20134","key":"10.1016\/j.compbiolchem.2025.108559_b5","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/S0167-8655(97)00179-7","article-title":"A graph distance metric based on the maximal common subgraph","volume":"19","author":"Bunke","year":"1998","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.compbiolchem.2025.108559_b6","series-title":"Chemberta: Large-scale self-supervised pretraining for molecular property prediction","author":"Chithrananda","year":"2020"},{"key":"10.1016\/j.compbiolchem.2025.108559_b7","series-title":"Research and Development in the Pharmaceutical Industry","author":"Congressional Budget Office","year":"2021"},{"issue":"1","key":"10.1016\/j.compbiolchem.2025.108559_b8","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1186\/s13321-020-00460-5","article-title":"Molecular representations in AI-driven drug discovery: a review and practical guide","volume":"12","author":"David","year":"2020","journal-title":"J. Cheminformatics"},{"key":"10.1016\/j.compbiolchem.2025.108559_b9","first-page":"1","article-title":"Statistical comparisons of classifiers over multiple data sets","volume":"7","author":"Dem\u0161ar","year":"2006","journal-title":"J. Mach. Learn. Res."},{"issue":"1","key":"10.1016\/j.compbiolchem.2025.108559_b10","doi-asserted-by":"crossref","first-page":"6395","DOI":"10.1038\/s41467-023-41948-6","article-title":"A systematic study of key elements underlying molecular property prediction","volume":"14","author":"Deng","year":"2023","journal-title":"Nat. Commun."},{"issue":"1","key":"10.1016\/j.compbiolchem.2025.108559_b11","doi-asserted-by":"crossref","first-page":"1414","DOI":"10.1111\/cbdd.13518","article-title":"Beyond model interpretability using LDA and decision trees for \u03b1-amylase and \u03b1-glucosidase inhibitor classification studies","volume":"94","author":"Di\u00e9guez-Santana","year":"2019","journal-title":"Chem. Biol. Drug Des."},{"key":"10.1016\/j.compbiolchem.2025.108559_b12","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.jhealeco.2016.01.012","article-title":"Innovation in the pharmaceutical industry: new estimates of R & D costs","volume":"47","author":"DiMasi","year":"2016","journal-title":"J. Heal. Econ."},{"key":"10.1016\/j.compbiolchem.2025.108559_b13","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110366","article-title":"Survey of spectral clustering based on graph theory","author":"Ding","year":"2024","journal-title":"Pattern Recognit."},{"issue":"1","key":"10.1016\/j.compbiolchem.2025.108559_b14","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1214\/aoms\/1177731944","article-title":"A comparison of alternative tests of significance for the problem of m rankings","volume":"11","author":"Friedman","year":"1940","journal-title":"Ann. Math. Stat."},{"issue":"1","key":"10.1016\/j.compbiolchem.2025.108559_b15","doi-asserted-by":"crossref","first-page":"100","DOI":"10.2307\/2346830","article-title":"A k-means clustering algorithm","volume":"28","author":"Hartigan","year":"1979","journal-title":"Appl. Stat."},{"key":"10.1016\/j.compbiolchem.2025.108559_b16","series-title":"Smiles transformer: Pre-trained molecular fingerprint for low data drug discovery","author":"Honda","year":"2019"},{"key":"10.1016\/j.compbiolchem.2025.108559_b17","series-title":"Strategies for pre-training graph neural networks","author":"Hu","year":"2019"},{"issue":"9","key":"10.1016\/j.compbiolchem.2025.108559_b18","doi-asserted-by":"crossref","first-page":"4062","DOI":"10.1021\/acs.jmedchem.5b01746","article-title":"Computational exploration of molecular scaffolds in medicinal chemistry: Miniperspective","volume":"59","author":"Hu","year":"2016","journal-title":"J. Med. Chem."},{"key":"10.1016\/j.compbiolchem.2025.108559_b19","series-title":"Concepts and applications of molecular similarity","author":"Johnson","year":"1990"},{"issue":"6","key":"10.1016\/j.compbiolchem.2025.108559_b20","first-page":"505","article-title":"Modern 2D QSAR for drug discovery","volume":"4","author":"Lewis","year":"2014","journal-title":"Wiley Interdiscip. Rev.: Comput. Mol. Sci."},{"key":"10.1016\/j.compbiolchem.2025.108559_b21","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1007\/978-1-60761-839-3_2","article-title":"Molecular similarity measures","author":"Maggiora","year":"2011","journal-title":"Chemoinformatics Comput. Chem. Biol."},{"issue":"2","key":"10.1016\/j.compbiolchem.2025.108559_b22","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1080\/03602532.2020.1726944","article-title":"Entering the era of computationally driven drug development","volume":"52","author":"Maharao","year":"2020","journal-title":"Drug Metab. Rev."},{"issue":"19","key":"10.1016\/j.compbiolchem.2025.108559_b23","doi-asserted-by":"crossref","first-page":"4350","DOI":"10.1021\/jm020155c","article-title":"Do structurally similar molecules have similar biological activity?","volume":"45","author":"Martin","year":"2002","journal-title":"J. Med. Chem."},{"key":"10.1016\/j.compbiolchem.2025.108559_b24","first-page":"215","article-title":"Data clustering using particle swarm optimization","volume":"vol. 1","author":"Merwe","year":"2003"},{"issue":"4","key":"10.1016\/j.compbiolchem.2025.108559_b25","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1016\/j.trci.2017.10.005","article-title":"Drug discovery and development: Role of basic biological research","volume":"3","author":"Mohs","year":"2017","journal-title":"Alzheimer\u2019s Dement.: Transl. Res. Clin. Interv."},{"key":"10.1016\/j.compbiolchem.2025.108559_b26","doi-asserted-by":"crossref","DOI":"10.1016\/j.csbj.2024.07.003","article-title":"Artificial intelligence in antidiabetic drug discovery: The advances in QSAR and the prediction of \u03b1-glucosidase inhibitors","author":"Odugbemi","year":"2024","journal-title":"Comput. Struct. Biotechnol. J."},{"issue":"16","key":"10.1016\/j.compbiolchem.2025.108559_b27","doi-asserted-by":"crossref","first-page":"3049","DOI":"10.1021\/jm960290n","article-title":"Neighborhood behavior: a useful concept for validation of \u201cmolecular diversity\u201d descriptors","volume":"39","author":"Patterson","year":"1996","journal-title":"J. Med. Chem."},{"key":"10.1016\/j.compbiolchem.2025.108559_b28","first-page":"12559","article-title":"Self-supervised graph transformer on large-scale molecular data","volume":"33","author":"Rong","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"7958","key":"10.1016\/j.compbiolchem.2025.108559_b29","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1038\/s41586-023-05905-z","article-title":"Computational approaches streamlining drug discovery","volume":"616","author":"Sadybekov","year":"2023","journal-title":"Nature"},{"issue":"8","key":"10.1016\/j.compbiolchem.2025.108559_b30","doi-asserted-by":"crossref","first-page":"888","DOI":"10.1109\/34.868688","article-title":"Normalized cuts and image segmentation","volume":"22","author":"Shi","year":"2000","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"4","key":"10.1016\/j.compbiolchem.2025.108559_b31","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1007\/s11222-007-9033-z","article-title":"A tutorial on spectral clustering","volume":"17","author":"Von Luxburg","year":"2007","journal-title":"Stat. Comput."},{"issue":"9","key":"10.1016\/j.compbiolchem.2025.108559_b32","doi-asserted-by":"crossref","first-page":"937","DOI":"10.1080\/17460441.2021.1915982","article-title":"Critical assessment of AI in drug discovery","volume":"16","author":"Walters","year":"2021","journal-title":"Expert. Opin. Drug Discov."},{"key":"10.1016\/j.compbiolchem.2025.108559_b33","doi-asserted-by":"crossref","unstructured":"Wang, S., Guo, Y., Wang, Y., et al., 2019. Smiles-BERT: Large scale unsupervised pre-training for molecular property prediction. In: Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. pp. 429\u2013436.","DOI":"10.1145\/3307339.3342186"},{"issue":"7","key":"10.1016\/j.compbiolchem.2025.108559_b34","doi-asserted-by":"crossref","first-page":"1149","DOI":"10.1109\/TNN.2011.2147798","article-title":"Spectral clustering on multiple manifolds","volume":"22","author":"Wang","year":"2011","journal-title":"IEEE Trans. Neural Netw."},{"issue":"11","key":"10.1016\/j.compbiolchem.2025.108559_b35","doi-asserted-by":"crossref","first-page":"2713","DOI":"10.1021\/acs.jcim.2c00495","article-title":"Improving molecular contrastive learning via faulty negative mitigation and decomposed fragment contrast","volume":"62","author":"Wang","year":"2022","journal-title":"J. Chem. Inf. Model."},{"issue":"3","key":"10.1016\/j.compbiolchem.2025.108559_b36","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1038\/s42256-022-00447-x","article-title":"Molecular contrastive learning of representations via graph neural networks","volume":"4","author":"Wang","year":"2022","journal-title":"Nat. Mach. Intell."},{"issue":"2","key":"10.1016\/j.compbiolchem.2025.108559_b37","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1093\/biostatistics\/kxx069","article-title":"Estimation of clinical trial success rates and related parameters","volume":"20","author":"Wong","year":"2019","journal-title":"Biostatistics"},{"issue":"2","key":"10.1016\/j.compbiolchem.2025.108559_b38","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1039\/C7SC02664A","article-title":"MoleculeNet: a benchmark for molecular machine learning","volume":"9","author":"Wu","year":"2018","journal-title":"Chem. Sci."},{"key":"10.1016\/j.compbiolchem.2025.108559_b39","series-title":"Fuzzy sets, information and control","author":"Zadeh","year":"1965"},{"issue":"1","key":"10.1016\/j.compbiolchem.2025.108559_b40","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1038\/s42004-023-00825-5","article-title":"Hierarchical molecular graph self-supervised learning for property prediction","volume":"6","author":"Zang","year":"2023","journal-title":"Commun. Chem."},{"key":"10.1016\/j.compbiolchem.2025.108559_b41","first-page":"17","article-title":"Self-tuning spectral clustering","author":"Zelnik-Manor","year":"2004","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.compbiolchem.2025.108559_b42","doi-asserted-by":"crossref","unstructured":"Zhang, X., Wang, S., Zhu, F., et al., 2018. Seq3seq fingerprint: Towards end-to-end semi-supervised deep drug discovery. In: Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. pp. 404\u2013413.","DOI":"10.1145\/3233547.3233548"},{"key":"10.1016\/j.compbiolchem.2025.108559_b43","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1038\/s42256-025-00994-z","article-title":"Large language models for scientific discovery in molecular property prediction","volume":"7","author":"Zheng","year":"2025","journal-title":"Nat. Mach. Intell."}],"container-title":["Computational Biology and Chemistry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1476927125002191?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1476927125002191?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T10:41:33Z","timestamp":1779446493000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1476927125002191"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12]]},"references-count":43,"alternative-id":["S1476927125002191"],"URL":"https:\/\/doi.org\/10.1016\/j.compbiolchem.2025.108559","relation":{},"ISSN":["1476-9271"],"issn-type":[{"value":"1476-9271","type":"print"}],"subject":[],"published":{"date-parts":[[2025,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A systematic framework enhancing molecular screening efficiency in drug discovery via scaffold-driven fuzzy similarity and adaptive spectral clustering","name":"articletitle","label":"Article Title"},{"value":"Computational Biology and Chemistry","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.compbiolchem.2025.108559","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"108559"}}