Abstract
Peptide toxins in animals as part of the chemical arsenal for predation and/or protection, and they can also safeguard the host from pathogenic infections. Insects including the hymenopterans generate a battery of toxic bactericidal or bacteriostatic molecules which are small multifunctional, linear peptides that cause pain, have antimicrobial effects, and inflammatory processes . The toxins under the experiment are active against gram-positive, gram-negative bacteria and fungi. The present in silico study aims to predict the physicochemical attributes like molecular weight, theoretical pI, amino acid composition, extinction co-efficient, estimated half-life, instability index, aliphatic index and grand average of hydropathy (gravy) of wasps’ (class: Insecta; order: Hymenoptera) 11 wasp venom allergens through Expasy Protparam & Pepstat software tools. The secondary structures of the toxins were predicted using psi-Blast-based secondary structure prediction GOR4 tools revealing the % α helix, extended β strand, random coil and ambiguous state reflecting a comparative picture of physicochemical parameters of these defensins. 3D Homology modelling of these toxins was accomplished through Swiss-model webserver tool and validated through various in silico tools like ANOLEA, ProSA-web, QMean4 determining Z score, PROCHEK establishing the 3D models of these toxins. Use of Inter Pro, CDD, PROSITE, P fam, Tox DL, PrDOS software predicted the protein family, protein toxicity, protein disorder respectively. Scratch Protein Predictor software tools predicted cysteine – cysteine bonds. Docking of the eleven (11) wasp venom allergens individually with bacterial cell wall component N-acetylglucosamine was done by CB DOCK webserver resulting negative affinity scores reflecting towards the strong binding between the mentioned 11 toxins and N-acetylglucosamine indicating that the mentioned wasps’ toxin molecules might be used as potential antibacterial therapeutic molecules binding to N-acetylglucosamine leading to an avenue to the probable bacterial drug discovery.
Published Version
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