N-function Heterocycles as Promising Anticancer Agents: A Case Study with a Decision Model in a Fuzzy Environment

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dc.authoridOkten, Salih/0000-0001-9656-1803
dc.contributor.authorBulut, Merve
dc.contributor.authorOkten, Salih
dc.contributor.authorOzcan, Evrencan
dc.contributor.authorEren, Tamer
dc.date.accessioned2025-01-21T16:42:52Z
dc.date.available2025-01-21T16:42:52Z
dc.date.issued2024
dc.departmentKırıkkale Üniversitesi
dc.description.abstractObjective This study aimed to evaluate the data according to five accepted criteria for the effects of twenty promising anticancer agents on five different cancer types and determine the most effective compounds for further in vitro and in vivo studies with a multi-criteria decision-making method (MCDM), which rationalizes decision making in a fuzzy environment to avoid the high cost and time requirements of further preclinical and clinical studies.Methods Within the scope of the study, the weights of the five criteria were evaluated with the Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP), which is one of the multi-criteria decision-making methods, and a comparison was made with the criteria weights obtained as a result of the Complex Proportional Assessment (COPRAS) method. Moreover, the effects of criteria weights calculated with PFAHP on evaluating alternatives were analyzed using different scenarios.Results Experimentally, twenty N-heterocyclic quinoline derivatives with different substituents were identified as promising anticancer agents. In this study, the multi-criteria decision-making (MCDM) model was proposed to identify the most promising anticancer agents against all tested cell lines. Both the experimental and model results indicated that 20, 17, 19, and 7 are the most promising anticancer agents against the A549, HeLa, Hep3B, HT29, and MCF7 cell lines. Moreover, different scenarios were generated and analyzed to prove the consistency of the proposed methodology.Conclusion MCDM strongly suggests that compounds 20, 17, 19, and 7 can be further investigated for in vivo studies.
dc.identifier.doi10.2174/1570180819666220704110011
dc.identifier.endpage115
dc.identifier.issn1570-1808
dc.identifier.issn1875-628X
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85178267884
dc.identifier.scopusqualityQ3
dc.identifier.startpage101
dc.identifier.urihttps://doi.org/10.2174/1570180819666220704110011
dc.identifier.urihttps://hdl.handle.net/20.500.12587/25159
dc.identifier.volume21
dc.identifier.wosWOS:001134916100012
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherBentham Science Publ Ltd
dc.relation.ispartofLetters In Drug Design & Discovery
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241229
dc.subjectQuinoline; anticancer effect; IC50; LDH; pythagorean fuzzy sets; MCDM
dc.titleN-function Heterocycles as Promising Anticancer Agents: A Case Study with a Decision Model in a Fuzzy Environment
dc.typeArticle

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