Using in silico techniques: Isolation and characterization of an insect cuticle-degrading-protease gene from Beauveria bassiana

Abstract

Cuticle-degrading-proteases (CDPs) secreted by Beauveria spp. are pivotal biocontrol substances, possessing commercial potential for developing bio-pesticides. Therefore, a thoughtful and contemplative understanding and assessment of the structural and functional features of these proteases would markedly assist the development of biogenic pesticides. Computational molecular biology is a new facile alternative approach to the tedious experimental molecular biology; therefore, by using bioinformatics tools, we isolated and characterized an insect CDP gene from Beauveria bassiana 70 s.l. genomic DNA.The CDP gene (1240 bp with GeneBank accession no. KT804651.1) consisted of three introns and four CDS exons, and shared 74–100% sequence identity to the reference CDP genes. Its phylogenetic tree results showed a unique evolution pattern, and the predicted amino acid peptide (PAAP) consisted of 344 amino acid residues with pI, molecular weight, instability index, grand average hydropathicity value and aliphatic index of 7.2, 35.4 kDa, 24.45, −0.149, and 76.63, respectively. The gene possessed 74–89% amino acid sequence similarity to the 12 reference strains. Three motifs (Peptidase_S8 subtilase family) were detected in the PAAP, and the computed 3D structure possessed 79.09% structural identity to alkaline serine proteases. The PAAP had four (three serine proteases and one Pyridoxal-dependent decarboxylase) conserved domains, a disulfide bridge, two calcium binding sites, MY domain, and three predicted active sites in the serine family domains.These results will set the groundwork for further exploitation of proteases and understanding the mechanism of disease caused by cuticle-degrading-serine-proteases from entomopathogenic fungi.