Bioinformatics Analysis of Cereus-Derived Peptides Targeting β‑Lactamases and Bilayer Membrane from Klebsiella pneumoniae and Acinetobacter baumannii.

Antimicrobial resistance (AMR) represents a major global public health challenge, arising from the ability of microorganisms such as bacteria, fungi, and viruses to develop mechanisms that render them insensitive to conventional antibiotics. A key factor contributing to this problem is the production of β-lactamase enzymes, which confer resistance to multiple antibiotic classes and are associated with multidrug-resistant pathogens such as Pseudomonas aeruginosa, Acinetobacter baumannii, and Klebsiella pneumoniae, responsible for severe and often fatal hospital-acquired infections. In addition, the phospholipid membrane model was generated using CHARMM-GUI to provide insight into peptide-membrane interactions and their potential to induce membrane disruption. In this context, developing new therapeutic strategies, such as antimicrobial peptides (AMPs), has emerged as a promising alternative capable of acting against resistant microorganisms. This study investigates, through in silico analyses using tools such as Fpocket, FTsite, FTmap, and HADDOCK, to evaluate the interactions between five AMPs derived from Neotropical Cereus (mandacaru) species against β-lactamases from K. pneumoniae and A. baumannii. As a result, all five Cereus-derived AMPs showed favorable predicted interactions with β-lactamase interaction sites, and CF267 and CJ149 exhibited stable engagement with the phospholipid bilayer, supporting their potential to disrupt membranes in the simulated system. Docking analyses indicated favorable affinities for all peptides, with CF267 × 3RXX and CJ149 × 3RXX emerging as the most promising complexes due to their highly negative energy scores. These findings suggest favorable predicted interactions with β-lactamase binding regions, indicating potential molecular compatibility against AMR mechanisms in A. baumannii and K. pneumoniae. Upcoming in vitro assays will be essential to validate these predictions.