Prediction of the Receptorome for the Human-Infecting Virome.

Abstract:

:The virus receptors are key for the viral infection of host cells. Identification of the virus receptors is still challenging at present. Our previous study has shown that human virus receptor proteins have some unique features including high N-glycosylation level, high number of interaction partners and high expression level. Here, a random-forest model was built to identify human virus receptorome from human cell membrane proteins with an accepted accuracy based on the combination of the unique features of human virus receptors and protein sequences. A total of 1424 human cell membrane proteins were predicted to constitute the receptorome of the human-infecting virome. In addition, the combination of the random-forest model with protein-protein interactions between human and viruses predicted in previous studies enabled further prediction of the receptors for 693 human-infecting viruses, such as the enterovirus, norovirus and West Nile virus. Finally, the candidate alternative receptors of the SARS-CoV-2 were also predicted in this study. As far as we know, this study is the first attempt to predict the receptorome for the human-infecting virome and would greatly facilitate the identification of the receptors for viruses.

journal_name

Virol Sin

journal_title

Virologica Sinica

authors

Zhang Z,Ye S,Wu A,Jiang T,Peng Y

doi

10.1007/s12250-020-00259-6

subject

Has Abstract

pub_date

2020-07-28 00:00:00

eissn

1674-0769

issn

1995-820X

pii

10.1007/s12250-020-00259-6

pub_type

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