4D-QSAR investigation and pharmacophore identification of pyrrolo[2,1-c][1,4]benzodiazepines using electron conformational-genetic algorithm method

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dc.authoridKOKBUDAK, ZULBIYE/0000-0003-2413-9595
dc.contributor.authorOzalp, A.
dc.contributor.authorYavuz, S. C.
dc.contributor.authorSabanci, N.
dc.contributor.authorCopur, F.
dc.contributor.authorKokbudak, Z.
dc.contributor.authorSaripinar, E.
dc.date.accessioned2024-12-24T19:28:15Z
dc.date.available2024-12-24T19:28:15Z
dc.date.issued2016
dc.departmentSiirt Üniversitesi
dc.description.abstractIn this paper, we present the results of pharmacophore identification and bioactivity prediction for pyrrolo[2,1-c][1,4]benzodiazepine derivatives using the electron conformational-genetic algorithm (EC-GA) method as 4D-QSAR analysis. Using the data obtained from quantum chemical calculations at PM3/HF level, the electron conformational matrices of congruity (ECMC) were constructed by EMRE software. The ECMC of the lowest energy conformer of the compound with the highest activity was chosen as the template and compared with the ECMCs of the lowest energy conformer of the other compounds within given tolerances to reveal the electron conformational submatrix of activity (ECSA, i.e. pharmacophore) by ECSP software. A descriptor pool was generated taking into account the obtained pharmacophore. To predict the theoretical activity and select the best subset of variables affecting bioactivities, the nonlinear least square regression method and genetic algorithm were performed. For four types of activity including the GI(50), TGI, LC50 and IC50 of the pyrrolo[2,1-c][1,4] benzodiazepine series, the r(train)(2), r(test)(2) and q(2) values were 0.858, 0.810, 0.771; 0.853, 0.848, 0.787; 0.703, 0.787, 0.600; and 0.776, 0.722, 0.687, respectively.
dc.description.sponsorshipResearch Fund of Erciyes University [FBD-10-2980]; Scientific Technical Research Council of Turkey (TUBITAK) [105T396, 107T385]
dc.description.sponsorshipThis work was supported by the Research Fund of Erciyes University under [ grant number FBD-10-2980]; and the Scientific Technical Research Council of Turkey (TUBITAK) under [ grant number 105T396] and [ grant number 107T385].
dc.identifier.doi10.1080/1062936X.2016.1174152
dc.identifier.endpage342
dc.identifier.issn1062-936X
dc.identifier.issn1029-046X
dc.identifier.issue4
dc.identifier.pmid27121415
dc.identifier.scopus2-s2.0-84970028488
dc.identifier.scopusqualityQ2
dc.identifier.startpage317
dc.identifier.urihttps://doi.org/10.1080/1062936X.2016.1174152
dc.identifier.urihttps://hdl.handle.net/20.500.12604/6988
dc.identifier.volume27
dc.identifier.wosWOS:000375443100002
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherTaylor & Francis Ltd
dc.relation.ispartofSar and Qsar in Environmental Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241222
dc.subjectElectron conformational-genetic algorithm
dc.subjectpyrrolo[2, 1-c][1,4]benzodiazepines
dc.subject4D-QSAR
dc.subjectpharmacophore
dc.subjectgenetic algorithm
dc.subjectelectron conformational method
dc.title4D-QSAR investigation and pharmacophore identification of pyrrolo[2,1-c][1,4]benzodiazepines using electron conformational-genetic algorithm method
dc.typeArticle

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