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    DRUG LIKNESS FILTERS AND QSAR ANALYSIS OF CAMPHOR-BASED DIIMINES DERIVATIVES AS ANTIVIRAL AGENTS
    (university of eloued جامعة الوادي, 2020-01-01) W., Hamzi1,2; S., Belaidi3,*,; O., Oukil2,; N., Aoumeur2, 2; , . Medjahed2 S
    In the present study, Quantitative structure–activity relationship (QSAR) study has been applied on twenty-five molecules of camphor-based symmetric diimines. A Multiple Linear Regression (MLR) procedure was used to correlate the relationships between molecular descriptors and the biological activity of camphor-based symmetric diimine derivatives. The predictivity of the model was estimated by cross-validation with the leave-one-out method. Our results suggest a QSAR model based on the following descriptors: MW, HE, Pol, MR, MV, HBA, NRB, PSA, μ and Etotal, for the influenza virus reproduction inhibition to confirm the predictive power of the models. High correlation between experimental and predicted activities was observed, indicating good quality of the QSAR model.