Rouane A.Tchouar N.Kerassa A.Cinar M.Belaidi S.20.04.20192019-04-2020.04.20192019-04-2020181557-7910https://dx.doi.org/10.1166/jbns.2018.1511https://hdl.handle.net/20.500.12403/395Qualitative and Quantitative structure activity relationship (SAR/QSAR) analysis was applied to eighteen Quercetin derivatives using a combination of various physicochemical, steric, electronic, and structural molecular descriptors. A multiple linear regression (MLR) procedure was used to model the relationships between molecular descriptors and the chemotherapeutic activity of the Quercetin derivatives. The stepwise regression method was used to derive the most significant models as a calibration model for predicting the inhibitory activity of this class of molecules. The best QSAR models were further validated by a leave one out technique as well as by the calculation of statistical parameters for the established theoretical models. High agreement between experimental and predicted inhibitory values, obtained in the validation procedure, indicated the good quality of the derived QSAR models. Copyright © 2018 American Scientific Publishers All rights reservedeninfo:eu-repo/semantics/closedAccessChemotherapeutic activityMLRQSARQuercetin derivativesSARDyesFlavonoidsImpuritiesLinear regressionMolecular graphicsOrganic chemicalsPhenolsToxic materialsChemotherapeutic activityInhibitory activityMolecular descriptorsMultiple linear regressionsQSARQuantitative structure activity relationshipStatistical parametersStepwise regression methodComputational chemistryChemotherapeutic activityMLRQSARQuercetin derivativesSARDyesFlavonoidsImpuritiesLinear regressionMolecular graphicsOrganic chemicalsPhenolsToxic materialsChemotherapeutic activityInhibitory activityMolecular descriptorsMultiple linear regressionsQSARQuantitative structure activity relationshipStatistical parametersStepwise regression methodComputational chemistryArticle12227828310.1166/jbns.2018.15112-s2.0-85049138984N/A