Designing of a novel chimeric antimicrobial peptide against Acinetobacter baumannii using three different bioinformatics methods and evaluation of its antimicrobial activity in vitro.

Background and purpose: The study aimed to design new chimeric antimicrobial peptides targeting Acinetobacter baumannii, a widespread and growing global concern due to antibiotic resistance. Three bioinformatics-based methods were utilized for this purpose.

Experimental approach: To design new chimeric peptides targeting Acinetobacter baumannii, a group of peptides were initially selected and divided into two categories based on their scores and performance. The peptides were then combined through 3 methods: 1. combining sequences based on their secondary structure using GOR IV software; 2. grouping only the amino acid sequences involved in the formation of the target peptide helix structure using Accelrys DS visualizer software; and 3. combining the most similar parts of the peptides in terms of amino acid type and order using online AntiBP2 software. The sequence length was optimized, and some amino acids were substituted.

Findings/results: The M-CIT peptide was selected for synthesis in the first method, but it did not show significant activity against the target bacteria (MIC = 187.5 μM and MBC = 375 μM). In the second method, no suitable score was observed. However, the M-PEX12 peptide was synthesized in the second method, demonstrating antimicrobial activity against A. baumannii (MIC = 33.1 μM and MBC = 41.4 μM).

Conclusion and implications: Three methods were evaluated for designing new chimeric peptides, and the third method, which involved modifying the number of amino acids in the parental peptides while maintaining their similarity, was found to be the most suitable.