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

Abstract

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.

Synthesis of Quinolones and Zwitterionic Quinolonate Derivatives with Broad-Spectrum Antibiotic Activity

“…A mathematical–topological prediction model previously described by our research group was used to select theoretically active compounds against E. coli from a virtual combinatorial library of 1000 quinolones [ 7 , 8 ]. In total, 298 quinolones from the virtual combinatorial library were selected by the model as theoretically active against E. coli ( Figure 2 ) (see Supplementary Materials ).…”

“…In total, 298 quinolones from the virtual combinatorial library were selected by the model as theoretically active against E. coli (Figure 2) (see Supplementary Materials). As the model established, the selected molecules had a value for index Nclass between 11 and 16 and a value for the DF within the 0-28 range [7]. Nclass is a topological index that could be defined as the topological distance (number of axes) between the two furthest vertices of a graph through the shortest path [7].…”

“…4.1.3. 1-cyclopropyl-6-fluoro-7-(1-methyl-1H-imidazol-4-yl)-4-oxo-1,4-dihydroquinoline-3carboxylic acid(7)…”

Quantitative structure–activity relationship methods in the discovery and development of antibacterials

“…5 It is here where quantitative structure-activity relationships (QSAR) methods play a key role, seeing as they provide useful information for the rational design of new molecules at a minimal cost. 6,7 QSAR is defined as a mathematical relationship linking chemical structures and pharmacological activity or other properties in a quantitative manner for a series of compounds. 8 Using QSAR methods for drug design has a series of advantages for the scientific community such as the decrease in spending on animal testing, sustainability, and economic and time-saving.…”

“…Moreover, WHO has also pointed out that investment for the development of new antimicrobial compounds is insufficient . It is here where quantitative structure–activity relationships (QSAR) methods play a key role, seeing as they provide useful information for the rational design of new molecules at a minimal cost . QSAR is defined as a mathematical relationship linking chemical structures and pharmacological activity or other properties in a quantitative manner for a series of compounds …”