Приказ основних података о документу

dc.creatorKovacević, Strahinja
dc.creatorKaradzić, Milica
dc.creatorPodunavac-Kuzmanović, Sanja
dc.creatorJevrić, Lidija
dc.creatorIvanović, Evica
dc.creatorVojnović, Matilda
dc.date.accessioned2020-12-17T22:11:34Z
dc.date.available2020-12-17T22:11:34Z
dc.date.issued2018
dc.identifier.issn1318-0207
dc.identifier.urihttp://aspace.agrif.bg.ac.rs/handle/123456789/4628
dc.description.abstractThe results presented in this study include the prediction of the antifungal activity of 24 oxazolo derivatives based on their topological and electrostatic molecular descriptors, derived from the 2D molecular structures. The artificial neural network (ANN) method was applied as a regression tool. The input data for ANN modeling were selected by stepwise selection (SS) procedure. The ANN modeling resulted in three networks with the outstanding statistical characteristics. High predictivity of the established networks was confirmed by comparisons of the predicted and experimental data and by the residuals analysis. The obtained results indicate the usefulness of the formed ANNs in precise prediction of minimum inhibitory concentrations of the analyzed compounds towards Candida albicans. The Sum of Ranking Differences (SRD) method was used in this study to reveal possible grouping of the compounds in the space of the variables used in ANN modeling. The obtained results can be considered to be a contribution to development of new antifungal drugs structurally based on oxazole core, particularly nowadays when there is a lack of highly efficient antimycotics.en
dc.publisherSlovensko Kemijsko Drustvo, Ljubljana
dc.relationinfo:eu-repo/grantAgreement/MESTD/Basic Research (BR or ON)/172012/RS//
dc.rightsopenAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceActa Chimica Slovenica
dc.subjectArtificial neural networksen
dc.subjectAntifungal activityen
dc.subjectMolecular topologyen
dc.subjectElectrostatic descriptorsen
dc.subjectQSARen
dc.subjectSum of Ranking Differencesen
dc.titleElectrostatic and Topological Features as Predictors of Antifungal Potential of Oxazolo Derivatives as Promising Compounds in Treatment of Infections Caused by Candida albicansen
dc.typearticle
dc.rights.licenseBY
dc.citation.epage491
dc.citation.issue3
dc.citation.other65(3): 483-491
dc.citation.rankM23
dc.citation.spage483
dc.citation.volume65
dc.identifier.doi10.17344/acsi.2017.3532
dc.identifier.fulltexthttp://aspace.agrif.bg.ac.rs/bitstream/id/3153/4625.pdf
dc.identifier.scopus2-s2.0-85061105476
dc.identifier.wos000444705500001
dc.type.versionpublishedVersion


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Приказ основних података о документу