Back

Network controllability enrichment analysis reveals that SARS-CoV-2 infection tends to target indispensable nodes of a directed human protein-protein interaction network

Lee, H.-J.

2021-04-19 systems biology
10.1101/2021.04.18.440358 bioRxiv
Show abstract

The COVID-19 disease has been a global threat caused by the new coronavirus species, SARS-CoV-2, since early 2020 with an urgent need for therapeutic interventions. In order to provide insight into human proteins targeted by SARS-CoV-2, here we study a directed human protein-protein interaction network (dhPPIN) based on our previous work on network controllability of virus targets. We previously showed that human proteins targeted by viruses tend to be those whose removal in a dhPPIN requires more control of the network dynamics, which were classified as indispensable nodes. In this study we introduce a more comprehensive rank-based enrichment analysis of our previous dhPPIN for SARS-CoV-2 infection and show that SARS-CoV-2 also tends to target indispensable nodes in the dhPPIN using multiple proteomics datasets, supporting validity and generality of controllability analysis of viral infection in humans. Also, we find differential controllability among SARS-CoV-2, SARS-CoV-1, and MERS-CoV from a comparative proteomics study. Moreover, we show functional significance of indispensable nodes by analyzing heterogeneous datasets from a genome-wide CRISPR screening study, a time-course phosphoproteomics study, and a genome-wide association study. Specifically, we identify SARS-CoV-2 ORF3A as most frequently interacting with indispensable proteins in the dhPPIN, which are enriched in TGF-beta signaling and tend to be sources nodes and interact with each other. Finally, we built an integrated network model of ORF3A-interacting indispensable proteins with multiple functional supports to provide hypotheses for experimental validation as well as therapeutic opportunities. Therefore, a sub-network of indispensable proteins targeted by SARS-CoV-2 could serve as a prioritized network of drug targets and a basis for further functional and mechanistic studies from a network controllability perspective.

Matching journals

The top 12 journals account for 50% of the predicted probability mass.

1
Journal of Proteome Research
215 papers in training set
Top 0.4%
8.4%
2
iScience
1063 papers in training set
Top 1%
6.4%
3
npj Systems Biology and Applications
99 papers in training set
Top 0.3%
4.8%
4
Genomics, Proteomics & Bioinformatics
171 papers in training set
Top 1%
4.8%
5
Computational and Structural Biotechnology Journal
216 papers in training set
Top 0.8%
4.8%
6
PLOS Computational Biology
1633 papers in training set
Top 9%
4.0%
7
Molecular Omics
21 papers in training set
Top 0.1%
4.0%
8
Science China Life Sciences
26 papers in training set
Top 0.4%
3.6%
9
Frontiers in Cell and Developmental Biology
218 papers in training set
Top 2%
2.9%
10
Scientific Reports
3102 papers in training set
Top 44%
2.7%
11
PROTEOMICS
35 papers in training set
Top 0.2%
2.6%
12
Journal of Genetics and Genomics
36 papers in training set
Top 0.7%
2.1%
50% of probability mass above
13
eLife
5422 papers in training set
Top 36%
2.1%
14
Frontiers in Molecular Biosciences
100 papers in training set
Top 1%
2.1%
15
Molecular & Cellular Proteomics
158 papers in training set
Top 0.9%
1.9%
16
Cell Reports
1338 papers in training set
Top 24%
1.7%
17
Briefings in Bioinformatics
326 papers in training set
Top 4%
1.7%
18
Nature Communications
4913 papers in training set
Top 51%
1.7%
19
Heliyon
146 papers in training set
Top 2%
1.7%
20
Signal Transduction and Targeted Therapy
29 papers in training set
Top 0.7%
1.7%
21
Biomolecules
95 papers in training set
Top 0.7%
1.5%
22
Journal of Molecular Biology
217 papers in training set
Top 2%
1.5%
23
Communications Biology
886 papers in training set
Top 14%
1.2%
24
Bioinformatics
1061 papers in training set
Top 8%
1.2%
25
Cells
232 papers in training set
Top 5%
0.9%
26
PLOS ONE
4510 papers in training set
Top 63%
0.9%
27
Analytical Chemistry
205 papers in training set
Top 2%
0.9%
28
mSystems
361 papers in training set
Top 7%
0.8%
29
Biology
43 papers in training set
Top 3%
0.7%
30
Computers in Biology and Medicine
120 papers in training set
Top 5%
0.7%