| Literature DB >> 29112936 |
Tom Kazmirchuk1, Kevin Dick2, Daniel J Burnside1, Brad Barnes2, Houman Moteshareie1, Maryam Hajikarimlou1, Katayoun Omidi1, Duale Ahmed3, Andrew Low1, Clara Lettl1, Mohsen Hooshyar1, Andrew Schoenrock4, Sylvain Pitre4, Mohan Babu5, Edana Cassol6, Bahram Samanfar7, Alex Wong1, Frank Dehne6, James R Green2, Ashkan Golshani8.
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.Entities:
Keywords: Anti-Zika virus peptides; Host-virus interactions; In silico drug design; Protein-protein interaction prediction; Synthetic peptide design
Mesh:
Substances:
Year: 2017 PMID: 29112936 DOI: 10.1016/j.compbiolchem.2017.10.011
Source DB: PubMed Journal: Comput Biol Chem ISSN: 1476-9271 Impact factor: 2.877