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This study aimed to identify phytochemicals from a\n                    <jats:italic>Sclerocarya birrea\u2013Nauclea latifolia\u2013Piper longum<\/jats:italic>\n                    mixture that may modulate this disease axis. Seven constituents were screened against AChE, BACE1, DPP4, glucokinase, GSK3\u03b2, and TACE using molecular docking and MM\u2010GBSA rescoring. Prioritized complexes underwent triplicate 100\u2010ns molecular dynamics simulations, post\u2010MD MM\u2010GBSA analysis, physicochemical\/ADMET profiling, and ligand\u2010based target prediction. Quercetin pentamethyl ether (QR\u2010PME) emerged as the principal computational hit: its GSK3\u03b2 and TACE complexes maintained stable structural and energetic behavior, with mean binding free energy estimates of \u221230.07\u2009\u00b1\u20090.06 and \u221234.24\u2009\u00b1\u20090.07\u2009kcal\/mol, respectively, matching those of the reference inhibitors (\u221230.05\u2009\u00b1\u20090.07 and \u221234.08\u2009\u00b1\u20090.06\u2009kcal\/mol). QR\u2010PME satisfied Lipinski criteria and showed predicted intestinal absorption, although CYP inhibition liability and low blood\u2013brain barrier permeability remain concerns. ABCG2 was its top predicted target, suggesting an experimentally unresolved link to amyloid\u2010\u03b2 transport. These findings generate a testable hypothesis that QR\u2010PME may engage the metabolic\u2013inflammatory\u2013tau network connecting T2DM and AD, supporting biochemical, cellular, pharmacokinetic, and in vivo validation before its therapeutic applicability can be established.\n                  <\/jats:p>","DOI":"10.1002\/open.70299","type":"journal-article","created":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T14:02:56Z","timestamp":1789480976000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Integrative In Silico Profiling of Major Phytochemicals From a\n                    <i>Sclerocarya birrea\u2013Nauclea latifolia\u2013Piper longum<\/i>\n                    Mixture: Docking, Molecular Dynamics, ADMET, and Ligand\u2010Based Target Prediction on Shared Pathways in Type 2 Diabetes Mellitus and Alzheimer's Disease"],"prefix":"10.1002","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3651-4762","authenticated-orcid":false,"given":"Jean Philippe Djientcheu","family":"Tientcheu","sequence":"first","affiliation":[{"name":"Department of Animal Biology and Physiology University of Yaound\u00e9 I  Yaound\u00e9 Cameroon"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2189-0703","authenticated-orcid":false,"given":"Erman Salih","family":"\u0130stifli","sequence":"additional","affiliation":[{"name":"Faculty of Science and Literature Department of Biology Cukurova University  Adana T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,15]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.14283\/jpad.2023.63"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.4239\/wjd.v12.i6.745"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140\u20106736(23)01301\u20106"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/S2468-2667(21)00249-8"},{"key":"e_1_2_10_6_1","first-page":"78","article-title":"In\u2010silico discovery of Dipeptidyl Peptidase\u20104 inhibitors from African Medicinal Plants: Molecular Docking, ADMET, Dynamics Simulation, and MM\u2010GBSA Analyses","volume":"69","author":"Akinwumi I. 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