QSAR-based Design of Schiff Base Inhibitors for Drug-resistant Salmonella typhi

Abstract

Salmonella typhi, a Gram-negative pathogen linked to typhoid disease, has shown concerning patterns of antibiotic resistance, highlighting the need for novel inhibitors. By using predicted Quantitative Structure-Activity Relationship (QSAR) models, this study aimed to identify the structural factors present in Schiff bases that have anti-Salmonella typhi activity. After a thorough collection of 43 Schiff bases was compiled, the minimum inhibitory concentrations (MIC) of each were transformed into pMIC values for analytical use. Molecular descriptors were obtained, and QSAR models were constructed using Genetic Function Approximation (GFA). Model 1 emerged as the most robust iteration, with validation metrics (R2 = 0.800, R2adj = 0.749, Q2 = 0.520, R2 - Q2 = 0.280, and R2pred = 0.642) reflecting substantial predictive capability. Model 1 identified Weta3.unity, a molecular weight descriptor, as the dominant descriptor that influences the anti-Salmonella typhi activity of Schiff bases. The findings highlight how molecular weight affects the efficacy of anti-Salmonella typhi, laying the groundwork for the logical development of more potent Schiff base derivatives.