{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T14:21:27Z","timestamp":1783347687232,"version":"3.54.6"},"reference-count":49,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T00:00:00Z","timestamp":1783123200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Metabolites"],"abstract":"<jats:p>Background\/Objectives: Diagnostic metabolites measured in newborn screening, inherited metabolic disease, lysosomal storage disease, oncometabolite testing and routine clinical biochemistry are direct read-outs of human metabolic state. Their mechanistic interpretation requires linking measured metabolites to enzymes, pathways, regulatory context, disease knowledge and, increasingly, AI-assisted quantitative systems pharmacology (AI-QSP) workflows. We developed EHMN2026\u00aeT as a license-aware AI-QSP integration framework that connects the EHMN2026\u00ae metabolic backbone with licensed geneXplain knowledge resources while keeping ownership, licensing and redistribution constraints explicit. Methods: EHMN2026\u00aeT integrates the SBML-encoded EHMN2026\u00ae metabolic backbone with licensed TRANSFAC\u00ae 2025.2, TRANSPATH\u00ae 2025.2 and HumanPSD\u2122 2025.2 resources. TRANSFAC\u00ae position weight matrices were used for promoter-level analysis of EHMN metabolic genes. The resulting transcription factor (TF)\u2013gene connections were mapped to EHMN genes, TRANSPATH\u00ae signalling\/molecular-state entries and HumanPSD\u2122 disease\/drug context. The framework is positioned as a controlled component of the IQANOVA AI-QSP environment, but only aggregate statistics, non-proprietary EHMN-derived summaries and manuscript-level examples are reported publicly unless separate permission is obtained from the relevant rightsholders. Results: Promoter analysis of 1681 EHMN2026\u00ae metabolic genes using 1147 mapped TRANSFAC\u00ae matrices identified 291,387 ENSG-level TF\u2013gene regulatory-potential connections involving 398 TFs and 1,107,264 predicted binding sites. The diagnostic panel contained 80 covered genes (63.5%), including complete coverage of oncometabolite enzymes and high coverage of organic acidaemia, steroidogenesis and fatty-acid oxidation categories. Mapping to TRANSPATH\u00ae expanded the EHMN genes into 144,529 molecular-state representations and 14,879 gene\u2013pathway or gene\u2013chain pairs. HumanPSD\u2122 was used as a licensed translational context layer; EHMN-specific HumanPSD\u2122 outputs are treated as license-controlled derived outputs and are therefore not redistributed as open detailed tables in this manuscript. Conclusions: EHMN2026\u00aeT provides a license-aware AI-QSP integration framework for tracing a diagnostic metabolite from a measured clinical value to candidate enzyme nodes, regulatory potential, signalling\/molecular-state context and disease or therapeutic interpretation. PWM-derived TF\u2013gene links are presented as regulatory hypotheses, not proof of active regulation. Public release should be limited to aggregate statistics and non-proprietary EHMN-derived components; detailed TRANSFAC\u00ae, TRANSPATH\u00ae and HumanPSD\u2122-derived edges, mappings, annotations and SBML outputs remain subject to geneXplain ownership and licensing terms.<\/jats:p>","DOI":"10.3390\/metabo16070469","type":"journal-article","created":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T12:01:37Z","timestamp":1783339297000},"page":"469","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["EHMN2026\u00aeT: A License-Aware AI-QSP Integration Framework Linking EHMN2026\u00ae with TRANSFAC\u00ae, TRANSPATH\u00ae and HumanPSD\u2122 for Diagnostic-Metabolite Interpretation"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8293-774X","authenticated-orcid":false,"given":"Igor","family":"Goryanin","sequence":"first","affiliation":[{"name":"School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK"},{"name":"IQANOVA Ltd., Edinburgh EH10 5LZ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leonid","family":"Slovianov","sequence":"additional","affiliation":[{"name":"IQANOVA Ltd., Edinburgh EH10 5LZ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Irina V.","family":"Goryanin","sequence":"additional","affiliation":[{"name":"IQANOVA Ltd., Edinburgh EH10 5LZ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6775-2467","authenticated-orcid":false,"given":"Alexander","family":"Kel","sequence":"additional","affiliation":[{"name":"geneXplain GmbH, 38300 Wolfenb\u00fcttel, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2304","DOI":"10.1056\/NEJMoa025225","article-title":"Screening newborns for inborn errors of metabolism by tandem mass spectrometry","volume":"348","author":"Wilcken","year":"2003","journal-title":"N. Engl. J. Med."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1053\/j.semperi.2015.03.002","article-title":"Current status of newborn screening worldwide: 2015","volume":"39","author":"Therrell","year":"2015","journal-title":"Semin. Perinatol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.pcl.2017.11.002","article-title":"Inborn errors of metabolism overview: Pathophysiology, manifestations, evaluation, and management","volume":"65","author":"Saudubray","year":"2018","journal-title":"Pediatr. Clin. N. Am."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2743","DOI":"10.1001\/jama.285.21.2743","article-title":"Enzyme replacement therapy in Fabry disease: A randomized controlled trial","volume":"285","author":"Schiffmann","year":"2001","journal-title":"JAMA"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"739","DOI":"10.1038\/nature08617","article-title":"Cancer-associated IDH1 mutations produce 2-hydroxyglutarate","volume":"462","author":"Dang","year":"2009","journal-title":"Nature"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1056\/NEJMoa0808710","article-title":"IDH1 and IDH2 mutations in gliomas","volume":"360","author":"Yan","year":"2009","journal-title":"N. Engl. J. Med."},{"key":"ref_7","first-page":"1","article-title":"Lysosomal storage diseases","volume":"2","author":"Ferreira","year":"2017","journal-title":"Transl. Sci. Rare Dis."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/S0003-2697(03)00056-3","article-title":"Analysis of a glucose tetrasaccharide elevated in Pompe disease by stable isotope dilution-electrospray ionization tandem mass spectrometry","volume":"316","author":"Young","year":"2003","journal-title":"Anal. Biochem."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"D622","DOI":"10.1093\/nar\/gkab1062","article-title":"HMDB 5.0: The Human Metabolome Database for 2022","volume":"50","author":"Wishart","year":"2022","journal-title":"Nucleic Acids Res."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1038\/nrm3314","article-title":"Innovation: Metabolomics: The apogee of the omics trilogy","volume":"13","author":"Patti","year":"2012","journal-title":"Nat. Rev. Mol. Cell Biol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"D545","DOI":"10.1093\/nar\/gkaa970","article-title":"KEGG: Integrating viruses and cellular organisms","volume":"49","author":"Kanehisa","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"ref_12","first-page":"D498","article-title":"The Reactome Pathway Knowledgebase","volume":"48","author":"Jassal","year":"2020","journal-title":"Nucleic Acids Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"D693","DOI":"10.1093\/nar\/gkab1016","article-title":"Rhea, the reaction knowledgebase in 2022","volume":"50","author":"Bansal","year":"2022","journal-title":"Nucleic Acids Res."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"The UniProt Consortium (2023). UniProt: The Universal Protein Knowledgebase in 2023. Nucleic Acids Res., 51, D523\u2013D531.","DOI":"10.1093\/nar\/gkac1052"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"D939","DOI":"10.1093\/nar\/gkaa980","article-title":"Genenames.org: The HGNC and VGNC resources in 2021","volume":"49","author":"Tweedie","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"D570","DOI":"10.1093\/nar\/gkaa992","article-title":"MetaNetX\/MNXref: Unified namespace for metabolites and biochemical reactions in the context of metabolic models","volume":"49","author":"Moretti","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"D1214","DOI":"10.1093\/nar\/gkv1031","article-title":"ChEBI in 2016: Improved services and an expanding collection of metabolites","volume":"44","author":"Hastings","year":"2016","journal-title":"Nucleic Acids Res."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1437","DOI":"10.1016\/j.cell.2017.10.049","article-title":"A next generation Connectivity Map: L1000 platform and the first 1,000,000 profiles","volume":"171","author":"Subramanian","year":"2017","journal-title":"Cell"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"D1074","DOI":"10.1093\/nar\/gkx1037","article-title":"DrugBank 5.0: A major update to the DrugBank database for 2018","volume":"46","author":"Wishart","year":"2018","journal-title":"Nucleic Acids Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"D789","DOI":"10.1093\/nar\/gku1205","article-title":"OMIM.org: Online Mendelian Inheritance in Man (OMIM), an online catalog of human genes and genetic disorders","volume":"43","author":"Amberger","year":"2015","journal-title":"Nucleic Acids Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"MSB4100177","DOI":"10.1038\/msb4100177","article-title":"The Edinburgh human metabolic network reconstruction and its functional analysis","volume":"3","author":"Ma","year":"2007","journal-title":"Mol. Syst. Biol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1777","DOI":"10.1073\/pnas.0610772104","article-title":"Global reconstruction of the human metabolic network based on genomic and bibliomic data","volume":"104","author":"Duarte","year":"2007","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"419","DOI":"10.1038\/nbt.2488","article-title":"A community-driven global reconstruction of human metabolism","volume":"31","author":"Thiele","year":"2013","journal-title":"Nat. Biotechnol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1038\/nbt.4072","article-title":"Recon3D enables a three-dimensional view of gene variation in human metabolism","volume":"36","author":"Brunk","year":"2018","journal-title":"Nat. Biotechnol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"eaaz1482","DOI":"10.1126\/scisignal.aaz1482","article-title":"An atlas of human metabolism","volume":"13","author":"Robinson","year":"2020","journal-title":"Sci. Signal."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Goryanin, I., Slovianov, L., Checkley, S., and Goryanin, I. (2026). EHMN 2026: A thermodynamically refined, SBML-standardised human metabolic network for genome-scale analysis and QSP integration. Metabolites, 16.","DOI":"10.20944\/preprints202602.1719.v1"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"e9110","DOI":"10.15252\/msb.20199110","article-title":"SBML Level 3: An extensible format for the exchange and reuse of biological models","volume":"16","author":"Keating","year":"2020","journal-title":"Mol. Syst. Biol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"20170082","DOI":"10.1515\/jib-2017-0082","article-title":"SBML Level 3 Package: Flux Balance Constraints, Version 2 Release 1","volume":"15","author":"Olivier","year":"2018","journal-title":"J. Integr. Bioinform."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1038\/s41596-018-0098-2","article-title":"Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v3.0","volume":"14","author":"Heirendt","year":"2019","journal-title":"Nat. Protoc."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Ebrahim, A., Lerman, J.A., Palsson, B.O., and Hyduke, D.R. (2013). COBRApy: COnstraints-Based Reconstruction and Analysis for Python. BMC Syst. Biol., 7.","DOI":"10.1186\/1752-0509-7-74"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1093\/nar\/24.1.238","article-title":"TRANSFAC: A database on transcription factors and their DNA binding sites","volume":"24","author":"Wingender","year":"1996","journal-title":"Nucleic Acids Res."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"D108","DOI":"10.1093\/nar\/gkj143","article-title":"TRANSFAC and its module TRANSCompel: Transcriptional gene regulation in eukaryotes","volume":"34","author":"Matys","year":"2006","journal-title":"Nucleic Acids Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1093\/bib\/bbn016","article-title":"The TRANSFAC project as an example of framework technology that supports the analysis of genomic regulation","volume":"9","author":"Wingender","year":"2008","journal-title":"Brief. Bioinform."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"650","DOI":"10.1016\/j.cell.2018.01.029","article-title":"The human transcription factors","volume":"172","author":"Lambert","year":"2018","journal-title":"Cell"},{"key":"ref_35","first-page":"D87","article-title":"JASPAR 2020: Update of the open-access database of transcription factor binding profiles","volume":"48","author":"Fornes","year":"2020","journal-title":"Nucleic Acids Res."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"ENCODE Project Consortium (2012). An integrated encyclopedia of DNA elements in the human genome. Nature, 489, 57\u201374.","DOI":"10.1038\/nature11247"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"D546","DOI":"10.1093\/nar\/gkj107","article-title":"TRANSPATH: An information resource for storing and visualizing signaling pathways and their pathological aberrations","volume":"34","author":"Krull","year":"2006","journal-title":"Nucleic Acids Res."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/S0168-9525(02)02556-8","article-title":"The TGF-beta-Smad network: Introducing bioinformatic tools","volume":"18","author":"Kloos","year":"2002","journal-title":"Trends Genet."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1093\/nar\/30.1.137","article-title":"Annotating the human proteome: The Human Proteome Survey Database (HumanPSD) and an in-depth target database for G protein-coupled receptors (GPCR-PD) from Incyte Genomics","volume":"30","author":"Hodges","year":"2002","journal-title":"Nucleic Acids Res."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Kel, A., Boyarskikh, U., Stegmaier, P., Leskov, L.S., Sokolov, A.V., Yevshin, I., Mandrik, N., Stelmashenko, D., Koschmann, J., and Kel-Margoulis, O. (2019). Walking pathways with positive feedback loops reveal DNA methylation biomarkers of colorectal cancer. BMC Bioinform., 20.","DOI":"10.1186\/s12859-019-2687-7"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"104448","DOI":"10.1016\/j.drudis.2025.104448","article-title":"Revolutionizing drug discovery: Integrating artificial intelligence with quantitative systems pharmacology","volume":"30","author":"Goryanin","year":"2025","journal-title":"Drug Discov. Today"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Leil, T.A., and Bertz, R. (2014). Quantitative systems pharmacology can reduce attrition and improve productivity in pharmaceutical research and development. Front. Pharmacol., 5.","DOI":"10.3389\/fphar.2014.00247"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1038\/s41573-019-0024-5","article-title":"Applications of machine learning in drug discovery and development","volume":"18","author":"Vamathevan","year":"2019","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1007\/s10928-013-9297-1","article-title":"Quantitative systems pharmacology as an extension of PK\/PD modeling in CNS research and development","volume":"40","author":"Geerts","year":"2013","journal-title":"J. Pharmacokinet. Pharmacodyn."},{"key":"ref_45","unstructured":"Sorger, P.K., Allerheiligen, S.R.B., Abernethy, D.R., Altman, R.B., Brouwer, K.L.R., Califano, A., D\u2019Argenio, D.Z., Iyengar, R., Jusko, W.J., and Lalonde, R. (2011). Quantitative and Systems Pharmacology in the Post-Genomic Era: New Approaches to Discovering Drugs and Understanding Therapeutic Mechanisms, NIH White Paper."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1038\/clpt.2013.40","article-title":"Systems pharmacology for drug discovery and development: Paradigm shift or flash in the pan?","volume":"93","author":"Vicini","year":"2013","journal-title":"Clin. Pharmacol. Ther."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2466","DOI":"10.1093\/bioinformatics\/btp465","article-title":"Network analyses in systems pharmacology","volume":"25","author":"Berger","year":"2009","journal-title":"Bioinformatics"},{"key":"ref_48","unstructured":"IQANOVA Ltd. (2026, May 28). AI-MIDD: Transforming Drug Development. Available online: https:\/\/www.iqanova.org\/."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Chen, E.Y., Tan, C.M., Kou, Y., Duan, Q., Wang, Z., Meirelles, G.V., Clark, N.R., and Ma\u2019ayan, A. (2013). Enrichr: Interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinform., 14.","DOI":"10.1186\/1471-2105-14-128"}],"container-title":["Metabolites"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-1989\/16\/7\/469\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T13:22:41Z","timestamp":1783344161000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-1989\/16\/7\/469"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,4]]},"references-count":49,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2026,7]]}},"alternative-id":["metabo16070469"],"URL":"https:\/\/doi.org\/10.3390\/metabo16070469","relation":{},"ISSN":["2218-1989"],"issn-type":[{"value":"2218-1989","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,4]]}}}