Integrated machine learning, molecular dynamics, and DFT-based approach to elucidate the inhibitory effect of...

Salmonella enterica serovar Typhi, the etiological agent of Typhoid fever, remains a critical public health concern associated with high morbidity in many developing countries. The widespread emergence of multidrug-resistant (MDR) Salmonella Typhi strains against the fluoroquinolone group of antibiotics, particularly ciprofloxacin, poses a significant global therapeutic challenge with underlying resistance due to mutations in quinolone-resistance determining region (QRDR) of gyrA gene, encoding DNA gyrase subunit A (GyrA). In pursuit of alternative therapeutic candidates, the present study was designed to evaluate ciprofloxacin analogues against prevalent GyrA mutations (S83F, D87G, and D87N) to overcome fluoroquinolone resistance through machine learning (ML)-based approach. Based on Decision table algorithm with 78% predictive accuracy, 354 potential active ciprofloxacin analogues were identified from a dataset of 400 compounds. Following molecular docking against each mutant variant, top 10 analogues were screened out based on their higher binding affinity than the reference compound, from which 8 compounds revealed acceptable drug-likeness and ADMET properties. Notably, two analogue compounds (C1) and (C5) exhibited highest average binding affinities of -34.17 kJ/mol and -33.61 kJ/mol, respectively. These compounds further yielded validatory results in molecular dynamics (MD) simulation and binding-free energy analysis using Molecular mechanics/Poisson-Boltzmann surface area. Density functional theory (DFT) study of both the compounds indicated least HOMO-LUMO energy gaps, implying enhanced chemical reactivity. Additionally, MEP (Molecular electrostatic potential) surface mapping and Fukui function analysis revealed key reactive regions, supporting favourable binding orientations. Overall, the findings identify promising ciprofloxacin analogues as lead compounds against GyrA mutations, supporting the development of structurally optimised antimicrobial therapeutics.