QSAR analysis of salicylamide isosteres with the use of quantum chemical molecular descriptors

Quantitative relationships between the molecular structure and the biological activity of 49 isosteric salicylamide derivatives as potential antituberculotics with a new mechanism of action against three Mycobacterial strains were investigated. The molecular structures were represented by quantum chemical B3LYP/6-31G∗ based molecular descriptors. A resulting set of 220 molecular descriptors, including especially electronic properties, was statistically analyzed using multiple linear regression, resulting in acceptable and robust QSAR models. The best QSAR model was found for Mycobacterium tuberculosis (r2 = 0.92; q2 = 0.89), and somewhat less good QSAR models were found for Mycobacterium avium (r2 = 0.84; q2 = 0.78) and Mycobacterium kansasii (r2 = 0.80; q2 = 0.56). All QSAR models were cross-validated using the leave-10-out procedure.

Graphical abstractIsosteres of salicylamides as a potential group of new antituberculotics were analyzed by QSAR approach using DFT based molecular descriptors. The statistically proved QSAR models explain the antimycobacterial activities by five selected descriptors.Figure optionsDownload full-size imageDownload as PowerPoint slide