ABSTRACT
Pseudomonas aeruginosa (P. aeruginosa) is a highly infectious and antibiotic-resistant bacterium, which causes acute and chronic nosocomial infections. P. aeruginosa exhibits multidrug resistance due to the emergence of resistant mutants. The bacterium takes advantage of intrinsic and acquired resistance mechanisms to resist almost every antibiotic. To overcome the drug-resistance problem, there is a need to develop effective drugs against antibiotic-resistant mutants. Therefore, in this study, we selected the F533L mutation in PBP3 (penicillin-binding protein 3) because of its important role in ß-lactam recognition. To target this mutation, we screened 147 antibacterial compounds from PubChem through a machine-learning model developed based on the decision stump algorithm with 75.75% accuracy and filtered out 55 compounds. Subsequently, out of 55 compounds, 47 compounds were filtered based on their drug-like activity. These 47 compounds were subjected to virtual screening to obtain binding affinity compounds. The binding affinity range of all 47 compounds was -11.3 to -4.6 kcal mol-1. The top 10 compounds were examined according to their binding with the mutation point. A molecular dynamic simulation of the top 8 compounds was conducted to understand the stability of the compounds containing the mutated PBP3. Out of 8 compounds, 3 compounds, namely, macozinone, antibacterial agent 71, and antibacterial agent 123, showed good stability and were validated by RMSD, RMSF, and binding-free analysis. The findings of this study revealed promising antibacterial compounds against the F533L mutant PBP3. Furthermore, developments in these compounds may pave the way for novel therapeutic interventions.
ABSTRACT
BACKGROUND: Neonatal sepsis poses a critical healthcare concern, as multidrug-resistant Klebsiella pneumoniae (K. pneumoniae) infections are on the rise. Understanding the antimicrobial susceptibility patterns and underlying resistance mechanism is crucial for effective treatment. OBJECTIVES: This study aimed to comprehensively investigate the antimicrobial susceptibility patterns of K. pneumoniae strains responsible for neonatal sepsis using in silico tools. We sought to identify trends and explore reasons for varying resistance levels, particularly for ß-lactams and fluoroquinolone. METHODS: K. pneumoniae isolated from neonates at Kanchi Kamakoti CHILDS Trust Hospital (2017-2020) were analyzed for antimicrobial resistance. Elevated resistance to ß-lactam and fluoroquinolone antibiotics was further investigated through molecular docking and interaction analysis. ß-lactam affinity with penicillin-binding proteins and ß-lactamases was examined. Mutations in ParC and GyrA responsible for quinolone resistance were introduced to investigate ciprofloxacin interactions. RESULTS: Of 111 K. pneumoniae blood sepsis isolates in neonates, high resistance was detected to ß-lactams such as cefixime (85.91%, n = 71), ceftriaxone (84.9%, n = 106), cefotaxime (84.9%, n = 82) and fluoroquinolone (ciprofloxacin- 79.44%, n = 107). Molecular docking revealed low ß-lactam binding toward penicillin-binding proteins and higher affinities for ß-lactamases, attributing to the reduced ß-lactam efficiency. Additionally, ciprofloxacin showed decreased affinity toward mutant ParC and GyrA in comparison to their corresponding wild-type proteins. CONCLUSION: Our study elucidates altered resistance profiles in neonatal sepsis caused by K. pneumoniae, highlighting mechanisms of ß-lactam and fluoroquinolone resistance. It underscores the urgent need for the development of sustainable therapeutic alternatives to address the rising antimicrobial resistance in neonatal sepsis.
