Artificial Neural Network and Multiple RegresAnalysis Applied to 2D-QSAR Studies: the Caof Imidazolidine-2,4-dione as PTP1B Inhibito

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dc.contributor.authorAggoun, Siham
dc.contributor.authorBelaidi, Salah
dc.contributor.authorGhamri, Meriam
dc.contributor.authorKerassa, Aicha
dc.contributor.authorÇinar, Mehmet
dc.contributor.authorYamari, Imane
dc.contributor.authorChtita, Samir
dc.date.accessioned2026-02-28T12:09:13Z
dc.date.available2026-02-28T12:09:13Z
dc.date.issued2024
dc.departmentBayburt Üniversitesi
dc.description.abstractIn this investigation, we undertook a comprehensive quantitative structure-activity relationship (QSAR) analysis using both modern artificial neural network (ANN) methods and classical multiple linear regression methods (MLR). Our primary focus was on revealing the intricate connection between antidiabetic activity and the molecular structure of thirty-nine imidazolidine-2,4-dione derivatives. The B3LYP hybrid functional and 6-31G (d) basis set computed electronic properties at the quantum level. Rigorous benchmarking against experimental data validated the reliability of our quantum theory approach. Our statistical model effectively predicted activities closely aligned with experimental antidiabetic activities, quantified by the IC<inf>50</inf> values. They also revealed a significant superiority of the ANN architecture (6-4-1) over the MLR method. This study stands as a meaningful contribution to the field, providing valuable insights for designing new antidiabetic drugs, particularly as potential inhibitors of tyrosine phosphate 1B (PTP1B). The explicit articulation of our primary aim and emphasis on the study’s significance underscore its potential impact on advancing drug development within the realm of antidiabetic therapeutics. © 2024, Department of Science and Technology. All rights reserved.
dc.identifier.endpage346
dc.identifier.issn00317683
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85186603532
dc.identifier.scopusqualityQ2
dc.identifier.startpage333
dc.identifier.urihttps://hdl.handle.net/20.500.12403/5890
dc.identifier.volume153
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherDepartment of Science and Technology
dc.relation.ispartofPhilippine Journal of Science
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260218
dc.subject(PTP1B)
dc.subject4-dione
dc.subjectantidiabetic
dc.subjectimidazolidine-2
dc.subjectMLR-ANN model
dc.subjectQSAR
dc.titleArtificial Neural Network and Multiple RegresAnalysis Applied to 2D-QSAR Studies: the Caof Imidazolidine-2,4-dione as PTP1B Inhibito
dc.typeArticle

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