Identification and characterization of new putative antimicrobial peptides from scorpion Chaerilus tricostatus revealed by in silico analysis and structure modeling

Antimicrobial peptides (AMPs) are considered a promising therapeutic strategy because of their high potential for fighting against antibiotic-resistant pathogens. Scorpion venom is a rich resource of AMPs because of their biodiversity. Accordingly, we aimed to employ a bioinformatics-based approach to search for new putative AMPs from available omics datasets. The amino acid sequence of the peptide Ctriporin was used as query for a blast search in the UniProt and NCBI databases, resulting in the identification of 14 homologous peptides from scorpion venom. To predict antimicrobial activity, all sequences were analyzed using various machine learning-based algorithms on the Collection of Anti-Microbial Peptides (CAMP_R3) database. Furthermore, the online tools Antifp, AVPpred, and iACP were used to predict the antifungal, antiviral, and anticancer activity, respectively. The physicochemical properties were also evaluated by online tools and compared with Antimicrobial Peptide Database Calculator and Predictor (APD3). Finally, the three-dimensional structure modeling of the peptides Ctriporin, Ctri10036, Ctri9610, and Ctri10033 was performed using I-TASSER and PEP-FOLD 3.5. Our in silico analysis led to the identification of three new peptides with potential antimicrobial properties from the venom of the scorpion Chaerilus tricostatus, which can be suitable candidates for further experimental validation studies.