Drug likeness scoring and quantitative structure anaplastic lymphoma kinase (ALK) inhibitors activities relationships of pyrazolone derivatives

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dc.authorid57202732782
dc.authorid22136501900
dc.authorid6602639857
dc.authorid57194949202
dc.authorid15764678000
dc.contributor.authorOuadah K.
dc.contributor.authorTchouar N.
dc.contributor.authorBelaidi S.
dc.contributor.authorOukil O.
dc.contributor.authorCinar M.
dc.date.accessioned20.04.201910:49:12
dc.date.accessioned2019-04-20T21:43:06Z
dc.date.available20.04.201910:49:12
dc.date.available2019-04-20T21:43:06Z
dc.date.issued2018
dc.departmentBayburt Üniversitesien_US
dc.description.abstractSeries of twenty-four compounds was the field for applying multi-parameter optimization (MPO) methods and qualitative approximations of structural activity relationships in order to determine the role of various physico-chemical and quantum descriptors used in QSAR modeling as independent variables. Anaplastic lymphoma kinase (ALK) inhibitory activity was considered as a component in this study. In order to illustrate the quantitative relationships between the molecular descriptors and the activity of pyrazolone derivatives, we have applied a multiple linear regression (MLR) procedure. By adopting cross-validation with the leave-one-out method, we could estimate the predictability of models. Our results suggest a QSAR model based on the following descriptors: S, V, LogP, POL, Ref, HOMO, LUMO, E, , HBA, PSA and NRB, for the inhibitory activities against ALK. Results show high correlation between experimental and predicted activity values, indicating the validation and the good quality of the QSAR model. Copyright © 2018 American Scientific Publishers All rights reserved.en_US
dc.identifier.doi10.1166/jbns.2018.1513
dc.identifier.endpage259
dc.identifier.issn1557-7910
dc.identifier.issue2
dc.identifier.scopus2-s2.0-85049147588en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage250
dc.identifier.urihttps://dx.doi.org/10.1166/jbns.2018.1513
dc.identifier.urihttps://hdl.handle.net/20.500.12403/396
dc.identifier.volume12
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherAmerican Scientific Publishers
dc.relation.ispartofJournal of Bionanoscienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectALK
dc.subjectMLR
dc.subjectPyrazolone
dc.subjectQSAR
dc.subjectSAR/SPR
dc.subjectEnzymes
dc.subjectLinear regression
dc.subjectMolecular graphics
dc.subjectOncology
dc.subjectAnaplastic lymphoma kinase
dc.subjectLeave one out methods
dc.subjectMulti-parameter optimizations
dc.subjectMultiple linear regressions
dc.subjectPyrazolones
dc.subjectQSAR
dc.subjectQuantitative structures
dc.subjectSAR/SPR
dc.subjectComputational chemistry
dc.subjectALK
dc.subjectMLR
dc.subjectPyrazolone
dc.subjectQSAR
dc.subjectSAR/SPR
dc.subjectEnzymes
dc.subjectLinear regression
dc.subjectMolecular graphics
dc.subjectOncology
dc.subjectAnaplastic lymphoma kinase
dc.subjectLeave one out methods
dc.subjectMulti-parameter optimizations
dc.subjectMultiple linear regressions
dc.subjectPyrazolones
dc.subjectQSAR
dc.subjectQuantitative structures
dc.subjectSAR/SPR
dc.subjectComputational chemistry
dc.titleDrug likeness scoring and quantitative structure anaplastic lymphoma kinase (ALK) inhibitors activities relationships of pyrazolone derivativesen_US
dc.typeArticleen_US

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