Designing anti-Zika virus peptides derived from predicted human-Zika virus protein-protein interactions. (December 2017)

• Record Type: Journal Article
• Authors: Kazmirchuk, Tom; Dick, Kevin; Burnside, Daniel. J.; Barnes, Brad; Moteshareie, Houman; Hajikarimlou, Maryam; Omidi, Katayoun; Ahmed, Duale; Low, Andrew; Lettl, Clara; Hooshyar, Mohsen; Schoenrock, Andrew; Pitre, Sylvain; Babu, Mohan; Cassol, Edana; Samanfar, Bahram; Wong, Alex; Dehne, Frank; Green, James. R.; Golshani, Ashkan
• Is Part Of: Computational biology and chemistry. Volume 71(2017)
• Page Start: 180
• Page End: 187
• Publication Date: 2017-12
• Subjects: Synthetic peptide design -- Anti-Zika virus peptides -- In silico drug design -- Protein-protein interaction prediction -- Host-virus interactions; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2017.10.011
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: We predicted Protein–protein Interaction (PPIs) between humans and the Zika virus (ZIKV). Using two computational tools, we found 209 human protein candidates predicted to interact with the ZIKV. Of these 209, we produced a priority list of 25 high-likelihood human protein candidates to further investigate. From these top 25, we take the top 4 PPIs and designed inhibitory therapeutics which are hypothesized to inhibit the corresponding interacting ZIKV protein, potentially interrupting the ZIKV lifecycle. Abstract: 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.