Quantitative Structure antifungal Activity Relationship (QSAR) study of a series of Schiff bases derivatives from4- aminobenzenesulphonamide by DFT method

Abstract

1 N’dri Jean Stéphane, 1 Koné M. Guy-Richard, 1,2* Kodjo Charles Guillaume, 1 Affi Sopi Thomas, 3 Kablan Ahmont Landry Claude, 2 Ouattara Zana Adama and 1 Ziao Nahossé 1 Laboratoire de Thermodynamique et de Physico-Chimie du Milieu, UFR SFA, Université Nangui Abrogoua 02 BP 801 Abidjan 02, Côte-d’Ivoire, 2 Laboratoire de Chimie BioOrganique et de Substances Naturelles, Université Nangui Abrogoua, UFR-SFA, 02 B.P. 801 Abidjan 02 Côte-d’Ivoire, 3 UFR des Sciences Biologiques, Université Péléforo Gon Coulibaly de Korhogo, BP 1328 Korhogo, Côte d’Ivoire ABSTRACT : In this work we will focus on a series of Schiff bases derived from 4aminobenzenesulphonamide. By implementing quantum chemistry methods, at B3LYP/6-311 G (d, p) level, we have identified two QSAR models from quantum descriptors and antifungal activities against Candida albicans and Aspergillus niger strains that were accredited of good statistical performance. For model 1 statistical indicators were: correlation coefficient R 2 = 0.984, standard deviation S=0.514 , Fischer test F=90.753 and the correlation coefficient of cross-validation QCV 2 = 0.983. Wereas the statistical datas of model 2 were: correlation coefficient R 2 =0.952, standard deviation S=0.596, Fischer test F=79.022 and the correlation coefficient of crossvalidation QCV 2 = 0.951. These two models showed that quantum descriptors namely dipole moment and index of electrophilie were the bases for antifungal activity of these Schiff bases. These models were validated with the criteria of acceptance Eriksson et al. for training set and Tropsha et al. for the validation set.