{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T23:51:20Z","timestamp":1789084280220,"version":"build-2803163510"},"reference-count":70,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T00:00:00Z","timestamp":1768867200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Office of Graduate Studies and Research"},{"name":"Becas Nacionales","award":["776575"],"award-info":[{"award-number":["776575"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Molecules"],"abstract":"<jats:p>The gut microbiome produces thousands of metabolites with potential to modulate central nervous system function through peripheral or direct neural mechanisms. Tourette syndrome, attention-deficit\/hyperactivity disorder, and autism spectrum disorder exhibit shared neurotransmitter dysregulation and microbiome alterations, yet mechanistic links between microbial metabolites and receptor-mediated neuromodulation remain unclear. We screened 27,642 microbiome SMILES metabolites for blood\u2013brain barrier permeability using rule-based SwissADME classification and a PyTorch 2.0 neural network trained on 7807 experimental compounds (test accuracy 86.2%, AUC 0.912). SwissADME identified 1696 BBB-crossing metabolites following Lipinski\u2019s criteria, while PyTorch classified 2484 metabolites with expanded physicochemical diversity. Following 3D conformational optimization (from SMILES) and curation based on \u226432 rotatable bonds, molecular docking was performed against five neurotransmitter receptors representing ionotropic (GABRA2, GRIA2, GRIN2B) and metabotropic (DRD4, HTR1A) receptor classes. The top 50 ligands across five receptors demonstrated method-specific BBB classification (44% SwissADME-only, 44% PyTorch-only, 12% overlap), validating complementary prediction approaches. Fungal metabolites from Ascomycota dominated high-affinity top ligands (66%) and menaquinone MK-7 showed broad phylogenetic conservation (71.4% of phylum). Our results establish detailed receptor\u2013metabolite interaction maps, with fungal metabolites dominating high-affinity ligands, challenging the prevailing bacterial focus of the microbiome and providing a foundation for precision medicine and a framework for developing microbiome-targeted therapeutics to address clinical needs in neurodevelopmental disorders.<\/jats:p>","DOI":"10.3390\/molecules31020366","type":"journal-article","created":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T14:57:58Z","timestamp":1768921078000},"page":"366","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Computational Identification of Blood\u2013Brain Barrier-Permeant Microbiome Metabolites with Binding Affinity to Neurotransmitter Receptors in Neurodevelopmental Disorders"],"prefix":"10.3390","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3416-1625","authenticated-orcid":false,"given":"Ricardo E.","family":"Buendia-Corona","sequence":"first","affiliation":[{"name":"Departamento de Ciencias Qu\u00edmico-Biol\u00f3gicas, Universidad de las Am\u00e9ricas Puebla, Puebla 72810, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1643-2059","authenticated-orcid":false,"given":"Mar\u00eda Fernanda","family":"Velasco Dey","sequence":"additional","affiliation":[{"name":"Facultad de Psicolog\u00eda, Benem\u00e9rita Universidad Aut\u00f3noma de Puebla, Puebla 72500, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9686-1623","authenticated-orcid":false,"given":"Lisset","family":"Valencia Robles","sequence":"additional","affiliation":[{"name":"Facultad de Psicolog\u00eda, Benem\u00e9rita Universidad Aut\u00f3noma de Puebla, Puebla 72500, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6872-8856","authenticated-orcid":false,"given":"Hannia Jossel\u00edn","family":"Hern\u00e1ndez-Biviano","sequence":"additional","affiliation":[{"name":"Facultad de Ciencias Biol\u00f3gicas, Benem\u00e9rita Universidad Aut\u00f3noma de Puebla, Puebla 72522, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3612-9581","authenticated-orcid":false,"given":"Cristina","family":"Hermosillo-Abundis","sequence":"additional","affiliation":[{"name":"Facultad de Psicolog\u00eda, Benem\u00e9rita Universidad Aut\u00f3noma de Puebla, Puebla 72500, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6724-6441","authenticated-orcid":false,"given":"Lucila Isabel","family":"Castro-Pastrana","sequence":"additional","affiliation":[{"name":"Escuela de Ciencias, Universidad de las Am\u00e9ricas Puebla, Ex Hacienda Sta. Catarina M\u00e1rtir S\/N, San Andr\u00e9s Cholula 72810, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Chen, Y., Xu, J., and Chen, Y. (2021). Regulation of Neurotransmitters by the Gut Microbiota and Effects on Cognition in Neurological Disorders. Nutrients, 13.","DOI":"10.3390\/nu13062099"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1877","DOI":"10.1152\/physrev.00018.2018","article-title":"The Microbiota-Gut-Brain Axis","volume":"99","author":"Cryan","year":"2019","journal-title":"Physiol. Rev."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1007\/s00018-021-04060-w","article-title":"The Microbiota\u2013Gut\u2013Brain Axis: Pathways to Better Brain Health. 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