4D-QSAR analysis and pharmacophore modeling: Electron conformational-genetic algorithm approach for penicillins

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dc.contributor.authorYanmaz, Ersin
dc.contributor.authorSaripinar, Emin
dc.contributor.authorSahin, Kader
dc.contributor.authorGecen, Nazmiye
dc.contributor.authorCopur, Fatih
dc.date.accessioned2024-12-24T19:25:22Z
dc.date.available2024-12-24T19:25:22Z
dc.date.issued2011
dc.departmentSiirt Üniversitesi
dc.description.abstract4D-QSAR studies were performed on a series of 87 penicillin analogues using the electron conformational-genetic algorithm (EC-GA) method. In this EC-based method, each conformation of the molecular system is described by a matrix (ECMC) with both electron structural parameters and interatomic distances as matrix elements. Multiple comparisons of these matrices within given tolerances for high active and low active penicillin compounds allow one to separate a smaller number of matrix elements (ECSA) which represent the pharmacophore groups. The effect of conformations was investigated building model 1 and 2 based on ensemble of conformers and single conformer, respectively. GA was used to select the most important descriptors and to predict the theoretical activity of the training (74 compounds) and test (13 compounds, commercial penicillins) sets. The model 1 for training and test sets obtained by optimum 12 parameters gave more satisfactory results (R-training(2) = 0.861, SEtraining = 0.044, R-test(2) = 0.892, SEtest = 0.099, q(2) = 0.702, q(ext1)(2) = 0.777 and q(ext2)(2) = 0.733) than model 2 (R-training(2) = 0.774, SEtraining = 0.056, R-test(2) = 0.840, SEtest = 0.121, q(2) = 0.514, q(ext1)(2) = 0.641 and q(ext2)(2) = 0.570). To estimate the individual influence of each of the molecular descriptors on biological activity, the E statistics technique was applied to the derived EC-GA model. (C) 2011 Elsevier Ltd. All rights reserved.
dc.description.sponsorshipScientific Technical Research Council of Turkey (TUBITAK) [107T385]
dc.description.sponsorshipThis project was financially supported by the Scientific Technical Research Council of Turkey (TUBITAK, Grant No. 107T385). The authors would like to thank Mustafa Yildirim and Serkan Sahin for their valuable suggestions.
dc.identifier.doi10.1016/j.bmc.2011.02.035
dc.identifier.endpage2210
dc.identifier.issn0968-0896
dc.identifier.issn1464-3391
dc.identifier.issue7
dc.identifier.pmid21419636
dc.identifier.scopus2-s2.0-79953204913
dc.identifier.scopusqualityQ1
dc.identifier.startpage2199
dc.identifier.urihttps://doi.org/10.1016/j.bmc.2011.02.035
dc.identifier.urihttps://hdl.handle.net/20.500.12604/6384
dc.identifier.volume19
dc.identifier.wosWOS:000288792400011
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherPergamon-Elsevier Science Ltd
dc.relation.ispartofBioorganic & Medicinal Chemistry
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241222
dc.subjectPenicillins
dc.subject4D-QSAR
dc.subjectDrug design
dc.subjectPharmacophore
dc.subjectElectron conformational
dc.subjectGenetic algorithm
dc.title4D-QSAR analysis and pharmacophore modeling: Electron conformational-genetic algorithm approach for penicillins
dc.typeArticle

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