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. 2022 Mar 7:20:1244-1253.
doi: 10.1016/j.csbj.2022.03.002. eCollection 2022.

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

Affiliations

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

Si Li et al. Comput Struct Biotechnol J. .

Abstract

The protein-protein interactions (PPIs) between human and viruses play important roles in viral infection and host immune responses. Rapid accumulation of experimentally validated human-virus PPIs provides an unprecedented opportunity to investigate the regulatory pattern of viral infection. However, we are still lack of knowledge about the regulatory patterns of human-virus interactions. We collected 27,293 experimentally validated human-virus PPIs, covering 8 virus families, 140 viral proteins and 6059 human proteins. Functional enrichment analysis revealed that the viral interacting proteins were likely to be enriched in cell cycle and immune-related pathways. Moreover, we analysed the topological features of the viral interacting proteins and found that they were likely to locate in central regions of human PPI network. Based on network proximity analyses of diseases genes and human-virus interactions in the human interactome, we revealed the associations between complex diseases and viral infections. Network analysis also implicated potential antiviral drugs that were further validated by text mining. Finally, we presented the Human-Virus Protein-Protein Interaction database (HVPPI, http://bio-bigdata.hrbmu.edu.cn/HVPPI), that provides experimentally validated human-virus PPIs as well as seamlessly integrates online functional analysis tools. In summary, comprehensive understanding the regulatory pattern of human-virus interactome will provide novel insights into fundamental infectious mechanism discovery and new antiviral therapy development.

Keywords: Antiviral therapy; Disease comorbidities; HVPPI; Network analysis; Protein-protein interactions.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

None
Graphical abstract
Fig. 1
Fig. 1
Overview of human–virus protein–protein interaction. A. Construction of the HVPPI resource for human–virus protein–protein interactions. B. Number of PPIs across 13 viruses. C. Box plots showing the number of interacting human proteins for each viral protein. D. Line charts showing the number of human proteins that interact with a different number of viral proteins across viruses.
Fig. 2
Fig. 2
Function enrichment of viral-interacting human proteins. (A) for SARS-CoV-1 and (B) for SARS-CoV-2. GO terms were clustered into groups based on gene similarities.
Fig. 3
Fig. 3
Virus-interacting proteins enriched in immune-related pathways. A. Circos plot showing the viral-interacting proteins annotated in different immune-related pathways. B. Network visualization of viral–human protein–protein interactions in antigen processing and presentation pathway. C. Network visualization of viral–human protein–protein interactions in antimicrobials pathway.
Fig. 4
Fig. 4
Topological features of viral-interacting proteins in human PPIs. A. Degree distributions of viral interacting proteins and other proteins. B. Betweenness distributions of viral interacting proteins and other proteins. C. Closeness distributions of viral interacting proteins and other proteins.
Fig. 5
Fig. 5
Association of viral infections and human complex diseases. A. Disease comorbidity measured by the network overlap between SARS-CoV-1 targets and 299 diseases. The dots represent diseases whose radius reflects the number of associated diseases genes. The diseases closest to the center, whose names are marked, are expected to have higher comorbidity with viral infection. (B) for SARS-CoV-2. C. Network visualization showing the protein–protein interactions among viral-interacting proteins and diseases-associated proteins. (C) for SARS-CoV-1 and central nervous systems disease and (D) for SARS-CoV-2 and central nervous systems disease.
Fig. 6
Fig. 6
Prioritization of potential antiviral drugs. A. Network-based method for prioritization of potential drugs. B. Number of potential drugs prioritized across viruses. C. Number of viruses that can potentially be targeted by drugs. D. Heat map showing the Z-scores of different drugs across viruses. (E) and (F). Network visualization of protein–protein interactions among viral-interacting proteins and drug targets. (E) for SARS-CoV-1 and (F) for SARS-CoV-2.
Fig. 7
Fig. 7
Usage of HVPPI resource for human–virus PPIs. A. Users can browse the PPIs in different viruses by virus names or by clicking on the virus figure. B. Users can query of PPIs by species of interest, and protein of interest. C. The results page for human–virus PPIs. D. Detail pages for human–virus PPIs, including basic information, function prediction, network visualization, and potential drugs. E. Download pages of HVPPI. F. Help pages of HVPPI.

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References

    1. Dyer M.D., Murali T.M., Sobral B.W. The landscape of human proteins interacting with viruses and other pathogens. PLoS Pathog. 2008;4 - PMC - PubMed
    1. Lian X., Yang X., Yang S., Zhang Z. Current status and future perspectives of computational studies on human-virus protein-protein interactions. Brief Bioinform. 2021 - PubMed
    1. Zhou Y., Hou Y., Shen J., Huang Y., Martin W., Cheng F. Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2. Cell Discov. 2020;6:14. - PMC - PubMed
    1. Fiscon G., Conte F., Farina L., Paci P. SAveRUNNER: a network-based algorithm for drug repurposing and its application to COVID-19. PLoS Comput Biol. 2021;17 - PMC - PubMed
    1. Nicod C., Banaei-Esfahani A., Collins B.C. Elucidation of host-pathogen protein-protein interactions to uncover mechanisms of host cell rewiring. Curr Opin Microbiol. 2017;39:7–15. - PMC - PubMed

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