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. 2023 Feb 25;11(3):549.
doi: 10.3390/vaccines11030549.

Assessment of GO-Based Protein Interaction Affinities in the Large-Scale Human-Coronavirus Family Interactome

Soumyendu Sekhar Bandyopadhyay  1   2 , Anup Kumar Halder  3 , Sovan Saha  4 , Piyali Chatterjee  5 , Mita Nasipuri  1 , Subhadip Basu  1
Affiliations

Assessment of GO-Based Protein Interaction Affinities in the Large-Scale Human-Coronavirus Family Interactome

Soumyendu Sekhar Bandyopadhyay et al. Vaccines (Basel). .

Abstract

SARS-CoV-2 is a novel coronavirus that replicates itself via interacting with the host proteins. As a result, identifying virus and host protein-protein interactions could help researchers better understand the virus disease transmission behavior and identify possible COVID-19 drugs. The International Committee on Virus Taxonomy has determined that nCoV is genetically 89% compared to the SARS-CoV epidemic in 2003. This paper focuses on assessing the host-pathogen protein interaction affinity of the coronavirus family, having 44 different variants. In light of these considerations, a GO-semantic scoring function is provided based on Gene Ontology (GO) graphs for determining the binding affinity of any two proteins at the organism level. Based on the availability of the GO annotation of the proteins, 11 viral variants, viz., SARS-CoV-2, SARS, MERS, Bat coronavirus HKU3, Bat coronavirus Rp3/2004, Bat coronavirus HKU5, Murine coronavirus, Bovine coronavirus, Rat coronavirus, Bat coronavirus HKU4, Bat coronavirus 133/2005, are considered from 44 viral variants. The fuzzy scoring function of the entire host-pathogen network has been processed with ~180 million potential interactions generated from 19,281 host proteins and around 242 viral proteins. ~4.5 million potential level one host-pathogen interactions are computed based on the estimated interaction affinity threshold. The resulting host-pathogen interactome is also validated with state-of-the-art experimental networks. The study has also been extended further toward the drug-repurposing study by analyzing the FDA-listed COVID drugs.

Keywords: COVID-19; COVID-19 drugs; COVID-19 variants; SARS-CoV-2; gene ontology; go-semantic score; protein–protein interaction network.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Schematic diagram of our proposed model. The coronavirus and human proteins’ interaction affinities are determined by the model using gene ontology information of the proteins. Three different GO-relationship graphs, CC, MF, and BP, are used to evaluate all GO pair-wise interaction affinities. A protein pair’s fuzzy interaction affinity is calculated using the three pair-wise scores of all GO-pair affinities.
Figure 2
Figure 2
Venn diagram of the number of vulnerable host proteins obtained from host–pathogen interaction for all selected coronavirus organisms at 0.1 fuzzy threshold value. (A). The intersection of host protein identified from SARS-CoV-2, SARS-CoV, and MER-CoV. (B). Intersected host proteins from Murine-CoV, Bovine-CoV, and Rat Coronavirus. (C). Intersected host proteins of different viral organisms of Bat Coronavirus.
Figure 3
Figure 3
Venn diagram of the number of vulnerable host proteins obtained from host–pathogen interaction for all selected coronavirus organisms at 0.001 fuzzy threshold value. (A). Intersection of host protein identified from SARS-CoV-2, SARS-CoV, and MER-CoV. (B). The intersected host proteins from Murine-CoV, Bovine-CoV, and Rat Coronavirus. (C). Intersected host proteins from different viral organisms of Bat Coronavirus.
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Grants and funding

This research received no external funding.
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