aug-MIA-QSAR modeling of antimicrobial activities and design of multi-target anilide derivatives

Abstract

The antibacterial activity against Bacillus subtilis, Staphylococcus aureus and Escherichia coli, as well as the an- tifungal activity against Aspergillus niger of a series of anilide derivatives have been modeled using augment- ed multivariate image analysis applied to quantitative structure–activity relationship (aug-MIA-QSAR). This QSAR approach is based on 2D molecular shape, as well as atomic sizes and colors to encode chemical, phys- ical and biological properties. Predictive models with r 2 from 0.65 to 0.83 were used to estimate the antimi- crobial activities of novel anilide analogs, which were built from the combination of substructures of the most active antimicrobial compounds along the series. Given the synergistic effect of different substituents to pro- vide new molecules, promising compounds were proposed, highlighting a considerable multi-antimicrobial activity.