Topological index Nclass as a factor determining the antibacterial activity of quinolones against Escherichia coli

Aim: Due to antibiotic resistance and the lack of investment in antimicrobial R&D, quantitative structure-activity relationship (SAR) methods appear as an ideal approach for the discovery of new antibiotics. Result & methodology: Molecular topology and linear discriminant analysis were used to construct a model to predict activity against Escherichia coli. This model establishes new SARs, of which, molecular size and complexity (Nclass), stand out for their discriminant power. This model was used for the virtual screening of the Index Merck database, with results showing a high success rate as well as a moderate restriction. Conclusion: The model efficiently finds new active compounds. The topological index Nclass can act as a filter in other quantitative structure-activity relationship models predicting activity against E. coli.