title: 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 antifungal activity against Aspergillus niger of a series of anilide derivatives have been modeled using augmented 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, physical and biological properties. Predictive models with r(2) from 0.65 to 0.83 were used to estimate the antimicrobial 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 provide new molecules, promising compounds were proposed, highlighting a considerable multi-antimicrobial activity.
authors.affiliation: Department of Food Science, Federal University of Lavras, P.O. Box 3037, 37200-000 Lavras, MG, Brazil. cleitonnunes@dca.ufla.br
authors.forename: Cleiton A
authors.initials: CA
authors.lastname: Nunes
authors.forename: Matheus P
authors.initials: MP
authors.lastname: Freitas
mesh_terms: D000813:Anilides / Q000737:chemistry / Q000494:pharmacology; D000900:Anti-Bacterial Agents / Q000737:chemistry / Q000494:pharmacology; D000935:Antifungal Agents / Q000737:chemistry / Q000494:pharmacology; D001234:Aspergillus niger / Q000187:drug effects; D001419:Bacteria / Q000187:drug effects; D007091:Image Processing, Computer-Assisted; D008958:Models, Molecular; D015999:Multivariate Analysis; D021281:Quantitative Structure-Activity Relationship
chemical_list: D000813:Anilides; D000900:Anti-Bacterial Agents; D000935:Antifungal Agents
keywords: Anilide derivatives; Antibacterial activity; Antifungal activity; Chemometrics; aug-MIA-QSAR