A dual functional inhibitory molecule to combat GyrA-ParC and associated mutants in fluoroquinolone-resistant Shigella flexneri causing shigellosis: an ML guided and quantum simulation-based in silico approach

Shigellosis is a significant threat to global public health, with an estimated 188 million cases resulting in high death rates, with the highest burden among children under 5 years old living in low and middle-income countries. The major treatment options historically have been fluoroquinolones, most commonly ciprofloxacin, and other antibiotics like azithromycin and third-generation cephalosporins. Fluoroquinolone-resistant S. flexneri poses an increased risk of causing disease globally and therefore represents a growing public health concern. Fluoroquinolone resistance in Shigella is primarily caused by chromosomal mutations in the DNA gyrase and topoisomerase IV subunits, which reduce the affinity of fluoroquinolones for their target sites, thereby reducing the effectiveness of therapy. In this study, we developed a machine-learning guided in silico approach to identify a single molecule capable of inhibiting both the DNA gyrase subunit A and topoisomerase IV, including resistant mutants, in Shigella flexneri . To accomplish this goal, machine learning models were trained on existing minimum inhibitory concentrations for various active compounds including different antibiotics against S. flexneri to screen a library of ciprofloxacin analogues derived from the PubChem database. The top-ranked compounds were then further evaluated utilising a multidisciplinary computational approach that included virtual screening, toxicity assessments, quantum simulations via density functional theory, molecular docking studies, molecular dynamic simulations, and binding free energy calculations. The multi-faceted computational workflow identified a lead compound, CA_1617 [PubChem CID: 1350066; IUPAC name: 6-Fluoro-1-(4-fluorophenyl)-7-(4-methyl-3-oxopiperazin-1-yl)-4-oxoquinoline-3-carboxylic acid] that demonstrated a high degree of dual-target affinity for both wild-type and mutant target proteins, had stable protein-ligand interactions, and had favourable pharmacokinetic characteristics relative to the reference antibiotic ciprofloxacin. These results support the potential of the lead molecule CA_1617 as a mutation-resistant inhibitor. However, additional experimental validation is required to determine its efficacy and translate the computational findings of this study into clinical use.