Unravelling mutation patterns in Extended-Spectrum β-Lactamases for precision drug design against AMR in Enterobacteriaceae.

Abstract

Antimicrobial resistance (AMR) presents a critical global challenge, causing over 1.27 million deaths annually, with projections reaching 10 million by 2050. Among the most concerning contributors are Enterobacteriaceae, particularly Escherichia coli and Klebsiella pneumoniae, which harbour Extended-Spectrum β-Lactamase (ESBL) genes-enzymes that hydrolyse β-lactam antibiotics and confer resistance-such as bla-CTX-M, bla-SHV, and bla-TEM. These genes confer resistance to β-lactam antibiotics, including penicillins and cephalosporins, limiting treatment options for urinary tract infections, bloodstream infections, and pneumonia. The World Health Organisation has classified these pathogens as critical targets for new drug development. In this study, we comprehensively analysed all known variants of bla-CTX-M, bla-SHV, and bla-TEM genes along with their wild-type sequences. Using a multi-step computational approach, we assessed guanine-cytosine (GC) content, single nucleotide polymorphisms (SNPs; single-base changes in DNA), insertion and deletion (InDel) variants (mutations involving nucleotide addition or removal), codon usage patterns, transcription factor binding sites (TFBS; DNA regions regulating gene expression), amino acid composition, protein stability, mutational hotspots, nucleotide and amino acid mutation frequencies, hydrophobicity, isoelectric point, aromaticity, aliphatic index, and molecular flexibility. The integrated dataset maps conserved regions and identifies residues frequently associated with resistance phenotypes. Our findings provide a framework for predicting resistance-associated mutation patterns and identifying genomic regions suitable for resistance-free drug targeting. These insights support prioritising drug target sites, optimising screening libraries, and generating high-quality datasets for machine learning-based precision drug design.