{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T16:38:44Z","timestamp":1780677524836,"version":"3.54.1"},"reference-count":48,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T00:00:00Z","timestamp":1758499200000},"content-version":"vor","delay-in-days":21,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Archiv der Pharmazie"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Dipeptidyl peptidase\u20104 inhibitors (DPP\u20104i) represent a relatively new class of oral antidiabetic drugs. This study focuses on: (a) identifying favourable and unfavourable fingerprints governing DPP\u20104 inhibition using fragment\u2010based analysis, (b) validating key fingerprints through HOMO\u2013LUMO gap analysis and electrostatic potential (ESP) maps, and (c) developing AI\/ML\u2010driven DPP\u20104 predictor, an online cheminformatics tool for efficient DPP\u20104i screening using a trained, validated AI\/ML model. The fragment\u2010based QSAR model finds key substructures linked to potent DPP\u20104 inhibition, including 2\u2010cyanopyrrolidine, 3\u2010amino tetrahydropyran, and difluoro phenyl groups. D0010 (3\u2010aminotetrahydropyran fingerprint G10) is the most reactive, while D0094 (difluorophenyl fingerprint G14) is the most stable, with D0012 and D0013 (2\u2010cyanopyrrolidine fingerprints G1, G5) offering a balance between stability and reactivity. In addition, the d4p_v1 tool (\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/github.com\/Amincheminfom\/d4p_v1\">https:\/\/github.com\/Amincheminfom\/d4p_v1<\/jats:ext-link>\n                    ) reliably distinguishes active and inactive DPP\u20104i using molecular descriptors derived from input SMILES strings. Therefore, this study not only revealed the chemical space of DPP\u20104i but also opened up a horizon in developing novel potent DPP\u20104i for the management of type 2 diabetes mellitus (T2DM) in the future.\n                  <\/jats:p>","DOI":"10.1002\/ardp.70106","type":"journal-article","created":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T06:47:31Z","timestamp":1758610051000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["AI\/ML\u2010Driven DPP\u20104 Inhibitor Predictor (d4p_v1) for Enhanced Type 2 Diabetes Mellitus Management: Insights Into Chemical Space, Fingerprints, and Electrostatic Potential Maps"],"prefix":"10.1002","volume":"358","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2759-9845","authenticated-orcid":false,"given":"Anu","family":"Manhas","sequence":"first","affiliation":[{"name":"Department of Chemistry, School of Energy Technology Pandit Deendayal Energy University Gandhinagar India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ritam","family":"Dutta","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Technology JIS University Kolkata West Bengal India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefano","family":"Piotto","sequence":"additional","affiliation":[{"name":"Department of Pharmacy University of Salerno Fisciano SA Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4799-7322","authenticated-orcid":false,"given":"Sk. Abdul","family":"Amin","sequence":"additional","affiliation":[{"name":"Department of Pharmacy University of Salerno Fisciano SA Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,9,22]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrdp.2015.19"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.3390\/biom14111479"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40264-019-00857-8"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.vph.2011.05.001"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2019.00389"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2019.00376"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.3803\/EnM.2022.605"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12272-016-0813-x"},{"key":"e_1_2_11_10_1","first-page":"471","article-title":"DPP\u20104 Inhibitors, Heart Failure and Type 2 Diabetes: All Eyes on Safety","volume":"5","author":"Paneni F.","year":"2015","journal-title":"Cardiovascular Diagnosis and Therapy"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.2337\/dc11-s229"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1517\/14740338.2014.944862"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bmc.2009.01.061"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-015-0069-3"},{"key":"e_1_2_11_15_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-018-0302-y"},{"key":"e_1_2_11_16_1","doi-asserted-by":"publisher","DOI":"10.1021\/ci8001414"},{"key":"e_1_2_11_17_1","doi-asserted-by":"publisher","DOI":"10.1080\/1062936X.2025.2514061"},{"key":"e_1_2_11_18_1","doi-asserted-by":"publisher","DOI":"10.1021\/jm9602928"},{"key":"e_1_2_11_19_1","doi-asserted-by":"publisher","DOI":"10.1021\/ci2001428"},{"key":"e_1_2_11_20_1","doi-asserted-by":"publisher","DOI":"10.3961\/jpmph.23.497"},{"key":"e_1_2_11_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bmcl.2005.03.077"},{"key":"e_1_2_11_22_1","doi-asserted-by":"publisher","DOI":"10.1080\/1062936X.2024.2366886"},{"key":"e_1_2_11_23_1","doi-asserted-by":"publisher","DOI":"10.1063\/1.1700523"},{"key":"e_1_2_11_24_1","doi-asserted-by":"publisher","DOI":"10.1021\/jp021152e"},{"key":"e_1_2_11_25_1","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jmedchem.2c00164"},{"key":"e_1_2_11_26_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41573-022-00542-z"},{"key":"e_1_2_11_27_1","doi-asserted-by":"publisher","DOI":"10.1021\/ja983494x"},{"key":"e_1_2_11_28_1","doi-asserted-by":"publisher","DOI":"10.1063\/1.436185"},{"key":"e_1_2_11_29_1","doi-asserted-by":"publisher","DOI":"10.3102\/1076998619832248"},{"key":"e_1_2_11_30_1","unstructured":"G.Van Rossum Python Programming Language USENIX Annual Technical Conference California USA 2007 pp.1\u201336."},{"key":"e_1_2_11_31_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-018-0258-y"},{"key":"e_1_2_11_32_1","first-page":"1007","article-title":"A Study on Mutual Information\u2010Based Feature Selection for Text Categorization","volume":"3","author":"Xu Y.","year":"2007","journal-title":"Journal of Computational Information Systems"},{"key":"e_1_2_11_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-27282-5_51"},{"key":"e_1_2_11_34_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ygeno.2012.04.003"},{"key":"e_1_2_11_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330701"},{"key":"e_1_2_11_36_1","doi-asserted-by":"publisher","DOI":"10.3390\/mi14020265"},{"key":"e_1_2_11_37_1","doi-asserted-by":"publisher","DOI":"10.1080\/1062936X.2016.1250229"},{"key":"e_1_2_11_38_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11030-025-11118-5"},{"key":"e_1_2_11_39_1","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkv1072"},{"key":"e_1_2_11_40_1","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkae1075"},{"key":"e_1_2_11_41_1","unstructured":"RDKit in Python 2024."},{"key":"e_1_2_11_42_1","doi-asserted-by":"publisher","DOI":"10.1021\/ci100050t"},{"key":"e_1_2_11_43_1","volume-title":"Discovery Studio 3.0 (DS 3.0)","year":"2015"},{"key":"e_1_2_11_44_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bpc.2025.107409"},{"key":"e_1_2_11_45_1","unstructured":"Gaussian 09 Gaussian Inc. 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