Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2018Scopus SJRQ3/r/bayburt/13753
  Qualitative and quantitative structure-activity relationships studies of quercetin derivatives as chemotherapeutic activity

  Rouane, Abderrahmane; Tchouar, Noureddine; Kerassa, Aicha; Cinar, Mehmet; Belaidi, Salah

  Qualitative 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.

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• MakaleYalnız künye2018Scopus SJRQ3/r/bayburt/12426
  Drug likeness scoring and quantitative structure anaplastic lymphoma kinase (ALK) inhibitors activities relationships of pyrazolone derivatives

  Ouadah, Karim; Tchouar, Noureddine; Belaidi, Salah; Oukil, Oualid; Cinar, Mehmet

  Series 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.

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