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Database Profile

General information

Full name: Human-Virus Interaction DataBase
Description: A comprehensive database for human-virus protein-protein interactions
Year founded: 2020
Last update:
Real time : Checking...
Country/Region: China
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Contact information

University/Institution: China Agricultural University
Address: State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, China.
Province/State: Beijing
Country/Region: China
Contact name (PI/Team): Xiaodi Yang
Contact email (PI/Helpdesk):


HVIDB: a comprehensive database for human-virus protein-protein interactions. [PMID: 33515030]
Xiaodi Yang, Xianyi Lian, Chen Fu, Stefan Wuchty, Shiping Yang, Ziding Zhang

While leading to millions of people's deaths every year the treatment of viral infectious diseases remains a huge public health challenge.Therefore, an in-depth understanding of human-virus protein-protein interactions (PPIs) as the molecular interface between a virus and its host cell is of paramount importance to obtain new insights into the pathogenesis of viral infections and development of antiviral therapeutic treatments. However, current human-virus PPI database resources are incomplete, lack annotation and usually do not provide the opportunity to computationally predict human-virus PPIs. Here, we present the Human-Virus Interaction DataBase (HVIDB, that provides comprehensively annotated human-virus PPI data as well as seamlessly integrates online PPI prediction tools. Currently, HVIDB highlights 48 643 experimentally verified human-virus PPIs covering 35 virus families, 6633 virally targeted host complexes, 3572 host dependency/restriction factors as well as 911 experimentally verified/predicted 3D complex structures of human-virus PPIs. Furthermore, our database resource provides tissue-specific expression profiles of 6790 human genes that are targeted by viruses and 129 Gene Expression Omnibus series of differentially expressed genes post-viral infections. Based on these multifaceted and annotated data, our database allows the users to easily obtain reliable information about PPIs of various human viruses and conduct an in-depth analysis of their inherent biological significance. In particular, HVIDB also integrates well-performing machine learning models to predict interactions between the human host and viral proteins that are based on (i) sequence embedding techniques, (ii) interolog mapping and (iii) domain-domain interaction inference. We anticipate that HVIDB will serve as a one-stop knowledge base to further guide hypothesis-driven experimental efforts to investigate human-virus relationships.

Brief Bioinform. 2021:() | 0 Citations (from Europe PMC, 2021-02-20)



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Created on: 2021-02-18
Curated by:
lin liu [2021-02-19]
Dong Zou [2021-02-18]