{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T01:32:27Z","timestamp":1793151147044,"version":"4.5.0"},"reference-count":37,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100007401","name":"Sri Ramachandra Institute of Higher Education and Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100007401","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":[[2026,12]]},"DOI":"10.1016\/j.compbiolchem.2026.109356","type":"journal-article","created":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T23:43:39Z","timestamp":1787701419000},"page":"109356","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Rule-based labels versus experimental endpoints: A systematic assessment of generalisation in QSAR models for ADMET prediction using fruit phytochemicals"],"prefix":"10.1016","volume":"125","author":[{"given":"Sandhiya","family":"Prabhakar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Poojhashri","family":"Jayagopal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J. Jino","family":"Blessy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.compbiolchem.2026.109356_bib1","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.nbd.2009.07.030","article-title":"Structure and function of the blood-brain barrier","volume":"37","author":"Abbott","year":"2010","journal-title":"Neurobiol. Dis."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib2","doi-asserted-by":"crossref","first-page":"4942","DOI":"10.1021\/jm990017w","article-title":"Designing libraries with CNS activity","volume":"42","author":"Ajay","year":"1999","journal-title":"J. Med. Chem."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib3","doi-asserted-by":"crossref","first-page":"880","DOI":"10.1016\/0006-291X(91)91647-U","article-title":"Correlation between oral drug absorption in humans and apparent drug permeability coefficients in human intestinal epithelial (Caco-2) cells","volume":"175","author":"Artursson","year":"1991","journal-title":"Biochem. Biophys. Res. Commun."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib4","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib5","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","article-title":"SMOTE: synthetic minority over-sampling technique","volume":"16","author":"Chawla","year":"2002","journal-title":"J. Artif. Intell. Res."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib6","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1145\/2939672.2939785","article-title":"XGBoost: a scalable tree boosting system","author":"Chen","year":"2016","journal-title":"Proc. 22nd ACM SIGKDD Int. Conf. Knowl. Discov. Data Min."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib7","doi-asserted-by":"crossref","first-page":"807","DOI":"10.1021\/js9804011","article-title":"Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. 1. Prediction of intestinal absorption","volume":"88","author":"Clark","year":"1999","journal-title":"J. Pharm. Sci."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib8","doi-asserted-by":"crossref","DOI":"10.1038\/srep42717","article-title":"SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules","volume":"7","author":"Daina","year":"2017","journal-title":"Sci. Rep."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib9","doi-asserted-by":"crossref","first-page":"1998","DOI":"10.3390\/pharmaceutics14101998","article-title":"Reliable prediction of Caco-2 permeability by supervised recursive machine learning approaches","volume":"14","author":"Falc\u00f3n-Cano","year":"2022","journal-title":"Pharmaceutics"},{"key":"10.1016\/j.compbiolchem.2026.109356_bib10","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1111\/j.1742-7843.2009.00517.x","article-title":"Active-site concentrations of chemicals - are they a better predictor of effect than plasma\/organ\/tissue concentrations?","volume":"106","author":"Hammarlund-Udenaes","year":"2010","journal-title":"Basic. Clin. Pharmacol. Toxicol."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib11","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1038\/nrd4510","article-title":"The re-emergence of natural products for drug discovery in the genomics era","volume":"14","author":"Harvey","year":"2015","journal-title":"Nat. Rev. Drug. Discov."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib12","doi-asserted-by":"crossref","first-page":"2408","DOI":"10.1021\/ci7002076","article-title":"ADME evaluation in drug discovery. 8. The prediction of human intestinal absorption by a support vector machine","volume":"47","author":"Hou","year":"2007","journal-title":"J. Chem. Inf. Model."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib13","article-title":"Predicting blood\u2013brain barrier permeability of molecules with a large language model and machine learning","volume":"14","author":"Huang","year":"2024","journal-title":"Sci. Rep."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib14","doi-asserted-by":"crossref","first-page":"D1388","DOI":"10.1093\/nar\/gkaa971","article-title":"PubChem in 2021: new data content and improved web interfaces","volume":"49","author":"Kim","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib15","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1038\/nrd1470","article-title":"Can the pharmaceutical industry reduce attrition rates?","volume":"3","author":"Kola","year":"2004","journal-title":"Nat. Rev. Drug. Discov."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib16","article-title":"Neurotherapeutics across blood\u2013brain barrier: screening of BBB-permeable and CNS-active molecules for neurodegenerative disease","volume":"16","author":"Kumar","year":"2025","journal-title":"Front. Pharmacol."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib17","unstructured":"Landrum, G., et al., 2024. RDKit: Open-source cheminformatics. https:\/\/www.rdkit.org (accessed 2024)."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib18","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/S0169-409X(96)00423-1","article-title":"Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings","volume":"23","author":"Lipinski","year":"1997","journal-title":"Adv. Drug. Deliv. Rev."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib19","doi-asserted-by":"crossref","first-page":"1242","DOI":"10.1021\/jm030408h","article-title":"Prediction of human volume of distribution values for neutral and basic drugs. 2. Extended data set and leave-class-out statistics","volume":"47","author":"Lombardo","year":"2004","journal-title":"J. Med. Chem."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib20","article-title":"A unified approach to interpreting model predictions","volume":"30","author":"Lundberg","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib21","doi-asserted-by":"crossref","first-page":"D930","DOI":"10.1093\/nar\/gky1075","article-title":"ChEMBL: towards direct deposition of bioassay data","volume":"47","author":"Mendez","year":"2019","journal-title":"Nucleic Acids Res."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib22","doi-asserted-by":"crossref","DOI":"10.1002\/minf.202400325","article-title":"Machine learning in drug development for neurological diseases: a review of blood brain barrier permeability prediction models","volume":"44","author":"Nabi","year":"2025","journal-title":"Mol. Inform."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib23","doi-asserted-by":"crossref","first-page":"770","DOI":"10.1021\/acs.jnatprod.9b01285","article-title":"Natural products as sources of new drugs over the nearly four decades from 01\/1981 to 09\/2019","volume":"83","author":"Newman","year":"2020","journal-title":"J. Nat. Prod."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib24","unstructured":"OECD, 2007. Guidance document on the validation of (Q)SAR models. OECD Series on Testing and Assessment, No. 69. OECD Publishing, Paris."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib25","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1602\/neurorx.2.4.541","article-title":"Medicinal chemical properties of successful central nervous system drugs","volume":"2","author":"Pajouhesh","year":"2005","journal-title":"NeuroRx"},{"key":"10.1016\/j.compbiolchem.2026.109356_bib26","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1021\/js950285r","article-title":"Correlation of drug absorption with molecular surface properties","volume":"85","author":"Palm","year":"1996","journal-title":"J. Pharm. Sci."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib27","doi-asserted-by":"crossref","first-page":"688","DOI":"10.1016\/j.cell.2020.01.021","article-title":"A deep learning approach to antibiotic discovery","volume":"180","author":"Stokes","year":"2020","journal-title":"Cell"},{"key":"10.1016\/j.compbiolchem.2026.109356_bib28","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1038\/nrd3187","article-title":"Coexistence of passive and carrier-mediated processes in drug transport","volume":"9","author":"Sugano","year":"2010","journal-title":"Nat. Rev. Drug. Discov."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib29","doi-asserted-by":"crossref","first-page":"3049","DOI":"10.1016\/j.apsb.2022.02.002","article-title":"Why 90% of clinical drug development fails and how to improve it?","volume":"12","author":"Sun","year":"2022","journal-title":"Acta Pharm. Sin. B"},{"key":"10.1016\/j.compbiolchem.2026.109356_bib30","doi-asserted-by":"crossref","first-page":"151","DOI":"10.3109\/10611869808997889","article-title":"Estimation of blood-brain barrier crossing of drugs using molecular size and shape, and H-bonding descriptors","volume":"6","author":"van de Waterbeemd","year":"1998","journal-title":"J. Drug. Target."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib31","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1021\/cn100008c","article-title":"Moving beyond rules: the development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of druglike properties","volume":"1","author":"Wager","year":"2010","journal-title":"ACS Chem. Neurosci."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib32","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1038\/s41392-023-01481-w","article-title":"The blood\u2013brain barrier: structure, regulation and drug delivery","volume":"8","author":"Wu","year":"2023","journal-title":"Signal. Transduct. Target. Ther."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib33","doi-asserted-by":"crossref","first-page":"W5","DOI":"10.1093\/nar\/gkab255","article-title":"ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties","volume":"49","author":"Xiong","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib34","doi-asserted-by":"crossref","first-page":"3370","DOI":"10.1021\/acs.jcim.9b00237","article-title":"Analyzing learned molecular representations for property prediction","volume":"59","author":"Yang","year":"2019","journal-title":"J. Chem. Inf. Model."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib35","doi-asserted-by":"crossref","first-page":"656","DOI":"10.1021\/jm00398a028","article-title":"Development of a new physicochemical model for brain penetration and its application to the design of centrally acting H2 receptor histamine antagonists","volume":"31","author":"Young","year":"1988","journal-title":"J. Med. Chem."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib36","doi-asserted-by":"crossref","first-page":"D1180","DOI":"10.1093\/nar\/gkad1004","article-title":"The ChEMBL database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods","volume":"52","author":"Zdrazil","year":"2024","journal-title":"Nucleic Acids Res."},{"key":"10.1016\/j.compbiolchem.2026.109356_bib37","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1002\/jps.1031","article-title":"Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors","volume":"90","author":"Zhao","year":"2001","journal-title":"J. Pharm. Sci."}],"container-title":["Computational Biology and Chemistry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1476927126004834?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1476927126004834?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T00:41:49Z","timestamp":1793148109000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1476927126004834"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":37,"alternative-id":["S1476927126004834"],"URL":"https:\/\/doi.org\/10.1016\/j.compbiolchem.2026.109356","relation":{},"ISSN":["1476-9271"],"issn-type":[{"value":"1476-9271","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Rule-based labels versus experimental endpoints: A systematic assessment of generalisation in QSAR models for ADMET prediction using fruit phytochemicals","name":"articletitle","label":"Article Title"},{"value":"Computational Biology and Chemistry","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.compbiolchem.2026.109356","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"109356"}}