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In silico prediction of the permeability of phytochemicals across the blood-brain barrier

2026-08-31Artigo científico Acesso aberto
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dc.contributor.authorCarregosa, Diogo
dc.contributor.authorMoreira, Iris
dc.contributor.authorRasteiro, Diogo
dc.contributor.authorVanneschi, Leonardo
dc.contributor.authorNunes dos Santos, Cláudia
dc.contributor.institutionProgramme in Translational Medicine (iNOVA4Health)
dc.contributor.institutionNOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
dc.contributor.institutioniNOVA4Health - pólo NMS
dc.contributor.institutionNOVA Institute for Medical Systems Biology
dc.contributor.institutionNOVA Information Management School (NOVA IMS)
dc.contributor.institutionInformation Management Research Center (MagIC) - NOVA Information Management School
dc.contributor.institutionInstituto de Tecnologia Química e Biológica António Xavier (ITQB)
dc.contributor.pblFrontiers Media
dc.date.accessioned2026-09-02T10:55:03Z
dc.date.available2026-09-02T10:55:03Z
dc.date.issued2026-08-31
dc.description
dc.description.abstractIntroduction: The role of phytochemicals like xanthines, and (poly)phenols in neurodegenerative diseases has been highly established and explored. However, the mechanism of these molecules to cross the membranes reaching the blood and the brain has largely been understudied. Methods: In this work, we used in silico methods to predict the permeability of more than 800 molecules across the membranes and specifically the blood-brain barrier. Our dataset included phytochemicals, like xanthine, phenolic terpenes, (poly)phenols and metabolites, including phase II conjugates, while some endogenous molecules and commercial drugs were used as positive/negative controls. We used QikProp to generate 42 computed physicochemical properties to predict the blood absorption, distribution to the brain, metabolism, and elimination of these molecules. Results: According to Qikprop 555 of 800 molecules were inside the range of 95% of known drugs for all computed properties, while through passive di[usion, 78 molecules may reach the blood and 52 may reach the brain parenchyma. Furthermore, using data from natural molecules present in human CSF samples, we used machine learning to build a model that was capable to predict 171 novel molecules with the potential to reach the brain environment. Conclusion: Overall, in this work we predicted the natural molecules with the potential to reach the brain, highlighting those that may do so by passive mechanisms. Our study creates an opportunity to track novel molecules in theblood and the brain and highlighting the most drug-promising natural molecules for brain drug development in the treatment and prevention of brain diseases.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent5460742
dc.identifier.doi10.3389/fddsv.2026.1939611
dc.identifier.issn2674-0338
dc.identifier.otherPURE: 172007164
dc.identifier.otherPURE UUID: b9c4c1f7-7165-446c-94b6-c5745b12e62f
dc.identifier.othercrossref: 10.3389/fddsv.2026.1939611
dc.identifier.otherORCID: /0000-0003-4732-3328/work/225619085
dc.identifier.otherORCID: /0000-0002-5809-1924/work/225620021
dc.identifier.urihttp://hdl.handle.net/10362/206000
dc.identifier.urlhttps://www.frontiersin.org/articles/10.3389/fddsv.2026.1939611/full
dc.language.isoeng
dc.peerreviewedyes
dc.relationhttps://doi.org/10.54499/UID/04152/2025
dc.relationhttps://doi.org/10.54499/UID/PRR/04152/2025
dc.subjectADME
dc.subjectBBB
dc.subjectdietary sources
dc.subjectnatural molecules
dc.subjectpassive diffusion
dc.subjectpredictions
dc.subjectQikProp
dc.subjectSDG 3 - Good Health and Well-being
dc.titleIn silico prediction of the permeability of phytochemicals across the blood-brain barrieren
dc.typejournal article
degois.publication.titleFrontiers in Drug Discovery
degois.publication.volume6
dspace.entity.typePublication
rcaap.rightsopenAccess

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