Chiépi Nadège Dominique Dou¹, Mamadou Guy-Richard Koné^{1, 2,}, Georges Stéphane Dembélé^{1, 2}, Doh Soro¹, Fandia Konaté¹, Nahossé Ziao^{1, 2}

The aim of this study is to develop a predictive model of the antidiabetic activity of a series of twenty-four (24) 1,3,4-thiadiazole molecules using quantum chemical methods. The molecules were optimised from the B3LYP/6-31+G (d, p) level of theory. The extracted descriptors are: bond length (l(C-N)), bond angle α(S-C-N); dipole moment (µ(D)) and standard entropy of formation (∆S⁰_f). This study was carried out quantitatively and qualitatively using the Multiple Linear Regression (RLM) and Non-Multiple Linear Regression (NMR) methods. Through this study, we have developed two regression models that are accredited with good statistical indicators. The statistical indicators of the model obtained by the RLM method are: the coefficient of determination R²= 0.931, the standard deviation S = 0.045, the Fischer coefficient F = 202.657, and the correlation coefficient of the cross-validation Q²cv=0.931. Those of the second model developed by the RLNM method are: R² =0.942; S of 0.048, F of 241.887 and Q²cv= 0.942. Furthermore, the bond angle α(S-C-N) is the priority descriptor for the prediction of the biological activity of the studied compounds. The acceptance criteria of Eriksson et al. used for the test set are verified. The external validation set was also verified for all criteria of Tropsha et al and Roy et al.

QSAR, RLM. RLNM, Antidiabetic activity, 1, 3, 4-thiadiazole derivatives