Discovery and computational characterization of ZIKV envelope-targeted peptides from a subtractive phage display library

TL;DR

Researchers identified specific peptides that bind to the Zika virus envelope protein, offering potential for accurate diagnostics and targeted treatments.

Contribution

A subtractive phage display approach identified high-affinity peptides with structural insights into their binding to ZIKV envelope protein.

Findings

Eight peptides with high binding affinity to ZIKV envelope protein were identified using subtractive phage display.

Molecular simulations revealed that four peptides bind specifically to the DIII domain via electrostatic interactions.

The peptides formed stable complexes over 300 ns of molecular dynamics simulations, indicating strong binding potential.

Abstract

The Zika virus (ZIKV) poses a significant public health threat, and developing highly specific diagnostic and therapeutic agents that can distinguish it from other flaviviruses remains a critical challenge. To address this, we utilized a phage display library with a strategic subtractive panning approach against the ZIKV envelope protein (ZIKV-pE). This method identified eight linear peptides with high binding ability for ZIKV-pE. Enzyme-linked immunosorbent assay (ELISA) confirmed that these peptides recognized ZIKV-pE with statistical significance compared to a bovine serum albumin (BSA) control. To elucidate the binding mechanisms, we performed molecular docking and molecular dynamics (MD) simulations. Computational analysis identified peptides R3Z15, R3Z09, R2Z05, and R3Z02 as the top candidates based on binding free energy calculations. The simulations revealed that these peptides bind specifically to the DIII domain of ZIKV-pE primarily via electrostatic interactions and form stable complexes over 300 ns of MD simulation. Our work identifies specific, high-affinity peptide binders to ZIKV-pE. It provides a structural basis for their selectivity, positioning them as promising candidates for the development of precise ZIKV diagnostics and targeted therapeutics.

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