Author: Halder, Anup Kumar; Dutta, Pritha; Kundu, Mahantapas; Basu, Subhadip; Nasipuri, Mita
Title: Review of computational methods for virus–host protein interaction prediction: a case study on novel Ebola–human interactions Cord-id: 72vya0vu Document date: 2017_9_26
ID: 72vya0vu
Snippet: Identification of potential virus–host interactions is useful and vital to control the highly infectious virus-caused diseases. This may contribute toward development of new drugs to treat the viral infections. Recently, database records of clinically and experimentally validated interactions between a small set of human proteins and Ebola virus (EBOV) have been published. Using the information of the known human interaction partners of EBOV, our main objective is to identify a set of proteins
Document: Identification of potential virus–host interactions is useful and vital to control the highly infectious virus-caused diseases. This may contribute toward development of new drugs to treat the viral infections. Recently, database records of clinically and experimentally validated interactions between a small set of human proteins and Ebola virus (EBOV) have been published. Using the information of the known human interaction partners of EBOV, our main objective is to identify a set of proteins that may interact with EBOV proteins. Here, we first review the state-of-the-art, computational methods used for prediction of novel virus–host interactions for infectious diseases followed by a case study on EBOV–human interactions. The assessment result shows that the predicted human host proteins are highly similar with known human interaction partners of EBOV in the context of structure and semantics and are responsible for similar biochemical activities, pathways and host–pathogen relationships.
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