The production of anti-Zika virus (ZIKV) therapeutics has become increasingly important as the propagation of the devastating virus continues largely unchecked. Notably, a causal relationship between ZIKV infection and neurodevelopmental abnormalities has been widely reported, yet a specific mechanism underlying impaired neurological development has not been identified. Here, we report on the design of several synthetic competitive inhibitory peptides against key pathogenic ZIKV proteins through the prediction of protein–protein interactions (PPIs). Often, PPIs between host and viral proteins are crucial for infection and pathogenesis, making them attractive targets for therapeutics. Using two complementary sequence-based PPI prediction tools, we first produced a comprehensive map of predicted human-ZIKV PPIs (involving 209 human protein candidates). We then designed several peptides intended to disrupt the corresponding host-pathogen interactions thereby acting as anti-ZIKV therapeutics. The data generated in this study constitute a foundational resource to aid in the multi-disciplinary effort to combat ZIKV infection, including the design of additional synthetic proteins.

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Keywords Anti-Zika virus peptides, Host-virus interactions, In silico drug design, Protein-protein interaction prediction, Synthetic peptide design
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Journal Computational Biology and Chemistry
Kazmirchuk, T. (Tom), Dick, K. (Kevin), Burnside, D.J. (Daniel. J.), Barnes, B. (Brad), Moteshareie, H. (Houman), Hajikarimlou, M. (Maryam), … Golshani, A. (2017). Designing anti-Zika virus peptides derived from predicted human-Zika virus protein-protein interactions. Computational Biology and Chemistry, 71, 180–187. doi:10.1016/j.compbiolchem.2017.10.011