Literature DB >> 33515030

HVIDB: a comprehensive database for human-virus protein-protein interactions.

Xiaodi Yang1, Xianyi Lian1, Chen Fu1, Stefan Wuchty2, Shiping Yang3, Ziding Zhang1.   

Abstract

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, http://zzdlab.com/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.
© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  annotation; database; human–virus interaction; prediction; protein–protein interaction

Year:  2021        PMID: 33515030     DOI: 10.1093/bib/bbaa425

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  9 in total

1.  mPPI: a database extension to visualize structural interactome in a one-to-many manner.

Authors:  Yekai Zhou; Hongjun Chen; Sida Li; Ming Chen
Journal:  Database (Oxford)       Date:  2021-06-22       Impact factor: 3.451

2.  Databases, Knowledgebases, and Software Tools for Virus Informatics.

Authors:  Yuxin Lin; Yulan Qian; Xin Qi; Bairong Shen
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 2.622

3.  Structure-based drug repurposing against COVID-19 and emerging infectious diseases: methods, resources and discoveries.

Authors:  Yosef Masoudi-Sobhanzadeh; Aysan Salemi; Mohammad M Pourseif; Behzad Jafari; Yadollah Omidi; Ali Masoudi-Nejad
Journal:  Brief Bioinform       Date:  2021-11-05       Impact factor: 11.622

4.  Comprehensive characterization of human-virus protein-protein interactions reveals disease comorbidities and potential antiviral drugs.

Authors:  Si Li; Weiwei Zhou; Donghao Li; Tao Pan; Jing Guo; Haozhe Zou; Zhanyu Tian; Kongning Li; Juan Xu; Xia Li; Yongsheng Li
Journal:  Comput Struct Biotechnol J       Date:  2022-03-07       Impact factor: 7.271

Review 5.  The Intricacy of the Viral-Human Protein Interaction Networks: Resources, Data, and Analyses.

Authors:  Deeya Saha; Marta Iannuccelli; Christine Brun; Andreas Zanzoni; Luana Licata
Journal:  Front Microbiol       Date:  2022-04-21       Impact factor: 5.640

6.  Deep Learning-Powered Prediction of Human-Virus Protein-Protein Interactions.

Authors:  Xiaodi Yang; Shiping Yang; Panyu Ren; Stefan Wuchty; Ziding Zhang
Journal:  Front Microbiol       Date:  2022-04-15       Impact factor: 6.064

Review 7.  The Landscape of Virus-Host Protein-Protein Interaction Databases.

Authors:  Gabriel Valiente
Journal:  Front Microbiol       Date:  2022-07-15       Impact factor: 6.064

8.  Virus-host interaction analysis in colorectal cancer identifies core virus network signature and small molecules.

Authors:  Sai Krishna A V S; Swati Sinha; Sainitin Donakonda
Journal:  Comput Struct Biotechnol J       Date:  2022-07-28       Impact factor: 6.155

9.  Cross-attention PHV: Prediction of human and virus protein-protein interactions using cross-attention-based neural networks.

Authors:  Sho Tsukiyama; Hiroyuki Kurata
Journal:  Comput Struct Biotechnol J       Date:  2022-10-08       Impact factor: 6.155

  9 in total

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