A Comprehensive In-Silico Pipeline for the Discovery of Non-toxic, Stable Antimicrobial Peptides From Databases for Targeting Multi-Drug Resistant K. pneumoniae

Abstract

The rapid emergence of multidrug-resistant Klebsiella pneumoniae has significantly reduced the effectiveness of conventional antibiotics, highlighting the need for alternative therapeutic strategies. This study employed a comprehensive in silico pipeline to identify antimicrobial peptides (AMPs) targeting the essential DNA replication initiator protein DnaA. A total of 28,361 peptide sequences were collected from publicly available AMP databases and sequentially filtered based on peptide length, net charge, GRAVY score, instability index, antimicrobial activity, toxicity, hemolytic potential, aggregation propensity, sequence similarity and favorable amphipathic properties. Four peptides satisfied all selection criteria and were subjected to structural prediction, membrane-binding analysis, protein–DNA docking, protein–peptide docking, and Normal Mode Analysis. Protein–DNA docking identified the functional DNA-binding residues of DnaA, while peptide docking demonstrated that all four peptides interacted within this region. Peptide 3 exhibited the strongest predicted interaction, with a binding energy of −61.8±5.1, a buried surface area of 1151.7±30.8 Å2, and seven hydrogen bonds with key DnaA residues. Normal Mode Analysis further supported the structural stability of the peptide–protein complexes. These findings identify four promising AMP candidates targeting DnaA and provide a computational framework for peptide prioritization against multidrug-resistant K. pneumoniae. However, the proposed interactions remain computational predictions and require experimental validation.