Exploring Aminopenicillin Resistance in Uropathogenic Staphylococcus species and Optimized Lead Prediction to Overcome Resistance through In-Silico Modules
Abstract
Penicillin resistance in uropathogenic Staphylococcus species, presents a significant challenge in treating urinary tract infections (UTIs), a prevalent global health concern. With resistance rates on the rise, particularly in developing countries, there is an urgent need to identify novel therapeutic alternatives. This study aims to investigate penicillin resistance in Staphylococcus species isolates and identify potential lead compounds using in-silico methods to optimize penicillin derivatives that can overcome resistance. A retrospective observational study of 3,000 UTI cases was conducted at a tertiary care hospital in Nepal, with 246 samples showing significant bacterial growth. Molecular docking using AutoDock 4.2 assessed the binding affinities of 37 novel penicillin derivatives against the penicillin-binding protein of S. aureus, PDB ID: 1TVF. Drug-protein interactions were analyzed using Discovery Studio, pharmacokinetics with SwissADME, and biological activity and toxicity predictions with PASS Online and ProTox-II, and molecular dynamics simulations by CABS-flex 2.0. Staphylococcus aureus was isolated in 6.5% of cases, with substantial resistance to cefoxitin (56.2%), ampicillin (50%), and amoxicillin (18.75%). Novel derivatives 2-6 Di-Nitro Amoxicillin Derivatives [BA-32] and 3,5 Di-Nitro Amoxicillin Derivatives [BA-33] exhibited superior binding affinities -8.1 and -8.2 kcal/mol compared to standard β-lactam antibiotics, forming stable interactions with key…
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