Ligand-based pharmacophore modeling targeting the fluoroquinolone antibiotics to identify potential antimicrobial compounds

Antibiotic resistance presents a serious challenge to global healthcare, making the discovery of new therapeutic agents crucial. In this study, we used pharmacophore modeling and virtual screening to identify potential lead compounds against drug-resistant bacteria. We developed a shared feature pharmacophore (SFP) map using four antibiotics—Ciprofloxacin, Delafloxacin, Levofloxacin, and Ofloxacin—and generated a drug library of 160,000 compounds from ZINCPharmer based on these features, which included hydrophobic areas, hydrogen bond acceptors (HBA), hydrogen bond donors (HBD), and aromatic moieties (Ar). Through virtual screening, we identified 25 potential drug compounds as hits, with fit scores ranging from 97.85 to 116 and RMSD values from 0.28 to 0.63. These hits were then subjected to molecular docking against the DNA gyrase subunit A protein (PDB ID: 4DDQ ), with ciprofloxacin as a control. The top five compounds—ZINC09133461, ZINC03791737, ZINC21983587, ZINC26469742, and ZINC26740199—achieved the highest docking scores, ranging from − 7.3 to − 7.4 kcal/mol and ciprofloxacin − 7.3 kcal/mol. After evaluating the drug-likeness of these compounds using Lipinski’s rule and analyzing their physicochemical properties, ZINC26740199 emerged as the most promising lead, offering hope in the fight against antibiotic resistance. Furthermore, molecular scaffold analysis revealed key similarities between ZINC26740199 and Ciprofloxacin, particularly in aromatic rings, hydrophobic regions, and hydrogen bond acceptors. These features suggest its potential as an effective antimicrobial agent, though further laboratory studies are needed to confirm its efficacy.