eng Science and Education Publishing Journal of Materials Physics and Chemistry 2333-4444 2022-10-16 10 2 49 58 10.12691/jmpc-10-2-3 JMPC20221023 article Chi¨¦pi Nad¨¨ge Dominique Dou 1 Mamadou Guy-Richard Kon¨¦ guyrichardkone@gmail.com 1 2 Georges St¨¦phane Demb¨¦l¨¦ 2 2 Doh Soro 2 Fandia Konat¨¦ 2 Nahoss¨¦ Ziao 2 2 Laboratoire de Thermodynamique et de Physico-Chimie du Milieu, Universit¨¦ NANGUI ABROGOUA, Abidjan, C?te-d¡¯Ivoire 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 ¦Á(S-C-N); dipole moment (µ(D)) and standard entropy of formation (?S0f). 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 ¦Á(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. http://pubs.sciepub.com/jmpc/10/2/3/jmpc-10-2-3.pdf QSAR RLM RLNM Antidiabetic activity 1 3 4-thiadiazole derivatives