Identification of Peptide Binders to Truncated Recombinant Chikungunya Virus Envelope Protein 2 Using Phage Display Technology and Their In Silico Characterization

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Abstract
Aim: To identify and characterize peptide binders to truncated recombinant chikungunya virus envelope protein 2. Background: Despite extensive research on the chikungunya virus (CHIKV), the specific antiviral treatment’s unavailability has stressed the need for the urgent development of therapeutics. The Envelope protein 2 (E2) of CHIKV that displays putative receptor binding sites and specific epitopes for virus neutralizing antibodies is a critical target for the therapeutic intervention. Objective: The study aims to identify the unique peptides that can bind to truncated E2 protein of CHIKV and further explore their properties as potential therapeutic candidate. Methods: A stretch of CHIKV-E2 (rE2), which is prominently exposed on the surface of virion, was used as bait protein to identify peptide binders to the CHIKV-rE2 using a 12-mer phage display peptide library. Three rounds of biopanning yielded several peptide binders to CHIKV-rE2 and their binding affinities were compared by phage ELISA. Additionally, a fully flexible-blind docking simulation investigated the possible binding modes of the selected peptides. Furthermore, the selected peptides were characterized and their ADMET properties were explored in silico. Results: Five peptides were identified as potential binders based on their robust reactivity to the bait protein. The selected peptides appeared to interact with the crucial residues that were notably exposed on the surface of E1-E2 trimeric structure. The explored in silico studies suggested their non-allergenicity, non-toxicity and likeliness to be antiviral. Conclusion: The potential binding peptides of CHIKV-rE2 protein were identified using phage display technology and characterized in silico. The selected peptides could be further used for the development of therapeutics against the CHIKV infection.
Funding Information
  • Department of Science and Technology (DST-INSPIRE (IF 150104))

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