In silico and in vitro analysis of resistance genes in Klebsiella pneumoniae for assessing antibiotic efficacy and identifying novel therapeutic targets.

Urinary tract infections (UTIs) represent a major public health concern worldwide, with Klebsiella pneumoniae emerging as a prominent uropathogen due to its rapidly increasing multidrug resistance. This study aimed to evaluate the phenotypic and molecular resistance profiles of K. pneumoniae isolated from UTI patients and to identify potential therapeutic targets using integrated in vitro and in silico approaches. Urine samples were collected from clinically suspected UTI patients. Isolates were confirmed as K. pneumoniae through standard morphological and biochemical characterization. Antimicrobial susceptibility testing was performed using the Kirby-Bauer disk diffusion method following Clinical and Laboratory Standards Institute (CLSI) guidelines. Molecular detection of resistance genes was carried out by polymerase chain reaction (PCR), while computational analyses including molecular docking, molecular dynamics simulations and ADMET profiling, were employed to evaluate potential drug candidates. Phenotypic analysis revealed high resistance rates to ampicillin, amoxicillin-clavulanate, cotrimoxazole, ciprofloxacin, and ceftriaxone, indicating a substantial prevalence of multidrug-resistant strains. Reduced susceptibility was observed against gentamicin, nitrofurantoin, fosfomycin, and imipenem, with emerging carbapenem resistance noted among the isolates. Molecular investigations identified the blaTEM gene as the most prevalent resistance determinant, strongly associated with β-lactam antibiotic resistance. In silico studies demonstrated stable binding interactions between selected ligands and the blaTEM protein, along with favorable pharmacokinetic and drug-likeness properties. In conclusion, this study highlights the significant contribution of multidrug-resistant K. pneumoniae to recurrent UTIs and underscores the importance of integrating phenotypic, molecular, and computational strategies to elucidate resistance mechanisms and facilitate the development of effective therapeutic interventions in clinical practice.