Abstract
Background: The purification of expressed proteins is the most critical part of subunit-- vaccine production. Protein-purification methods such as affinity chromatography and ion exchange still have the shortcomings of being time consuming and complicated. With the rapid development of computational molecular-simulation technology, structure-based peptide-ligand design has become feasible.
Objection: We aimed to apply molecular docking for a peptide ligand designed for classical swine fever virus (CSFV) E2 purification.
Methods: Computational-derived peptides were synthesized, and the in vitro binding interaction with E2 was investigated. The effects of purification on E2 were also evaluated.
Results: The best peptide recognizing E2 was P6, which had a sequence of KKFYWRYWEH. Based on kinetic surface plasmon resonance (SPR) analysis, the apparent affinity constant of P6 was found to be 148 nM. Importantly, P6 showed suitable binding affinity and specificity for E2 purification from transgenic rice seeds. Evaluation of immune antibodies in mice showed that the antibody- blocking rate on day 42 after inoculation reached 86.18% and 90.68%.
Conclusion: The computational-designed peptide in this study has high sensitivity and selectivity and is thus useful for the purification of CSFV E2. The novel method of design provided a broad platform and powerful tool for protein-peptide screening, as well as new insights into CSFV vaccine design.
Keywords: Classical swine fever virus, glycoprotein E2, computational design, affinity peptide ligand, purification, protein- peptide screening.
Graphical Abstract
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