Computationally Designed Peptides for Zika Virus Detection: An Incremental Construction Approach.

Area of Science:

• Virology
• Biotechnology
• Immunology

Background:

• Current anti-Zika virus (ZIKV) antibody production methods face limitations.
• Developing novel diagnostic tools for ZIKV detection is crucial.

Purpose of the Study:

• To propose a semi-combinatorial virtual strategy for selecting short peptides as biomimetic antibodies for intact ZIKV particle detection.
• To evaluate the efficacy of synthesized peptides in detecting ZIKV and discriminating it from Dengue virus (DENV).

Main Methods:

• A virtual strategy involving docking cycles of tetra, penta, hexa, and heptapeptide libraries was employed.
• Peptide libraries were designed to maximize discrimination between ZIKV and DENV envelope protein glycosylation sites.
• Synthesized peptides were tested against intact ZIKV and DENV particles using direct enzyme-linked immunosorbent assay (ELISA).

Main Results:

• Three synthesized peptides demonstrated good detection limits for intact ZIKV particles, with a dynamic range starting from 10^5 copies/mL.
• These peptides exhibited slight cross-reactivity with DENV serotypes at 10^6 copies/mL, but discrimination was lost at higher concentrations.
• Peptide sensitivity in biological matrices (serum, urine) decreased by one order of magnitude, with detection limits around 10^6 copies/mL for ZIKV.

Conclusions:

• The developed peptide-based assays show potential as sensitive diagnostic tools for ZIKV detection.
• These biomimetic antibodies offer a promising alternative to conventional antibodies for ZIKV diagnostics.
• Further research may optimize peptide sequences for enhanced specificity and sensitivity in clinical applications.