Preprint Article Version 2 This version is not peer-reviewed

Systems Biology Approach to Characterize Potential SARS-CoV-2 Pathways Based on Protein Functional Motifs

Version 1 : Received: 9 April 2020 / Approved: 10 April 2020 / Online: 10 April 2020 (13:22:27 CEST)
Version 2 : Received: 15 May 2020 / Approved: 16 May 2020 / Online: 16 May 2020 (18:54:17 CEST)

How to cite: Sobhy, H. Systems Biology Approach to Characterize Potential SARS-CoV-2 Pathways Based on Protein Functional Motifs. Preprints 2020, 2020040171 (doi: 10.20944/preprints202004.0171.v2). Sobhy, H. Systems Biology Approach to Characterize Potential SARS-CoV-2 Pathways Based on Protein Functional Motifs. Preprints 2020, 2020040171 (doi: 10.20944/preprints202004.0171.v2).

Abstract

Although phylogenetic analysis shows coronaviruses (CoV) share similar genome sequences, CoVs encode different number of proteins (5 to 14), which has implication on viral pathogenicity and infection. Here, we aimed to identify (in-silico) the similarities between different members of coronavirus family. The analysis included 50 coronavirus proteomes, including SARS-CoV-2 (COVID-19), to find the variation of the number of protein functional motifs and domain in each coronavirus. For this role, we used the experimentally validated domain (motif) that known to be crucial for viral infection. Although human CoVs are classified within one genus, we found variations among them. SARS-CoV-1, SARS-CoV-2 and MERS-CoV encode different type of domains, which has implications on the molecular interactions triggered by each virus within human cells. Secondly, we used functional motifs to reconstruct the potential molecular pathways or interactions triggered by SARS-CoV-2 proteins within human cell.

Subject Areas

protein functional domains; short linear motifs; coronaviruses; COVID-19; severe acute respiratory syndrome-related coronavirus; 2019-nCoV; virus outbreak

Comments (1)

Comment 1
Received: 16 May 2020
Commenter: Haitham Sobhy
Commenter's Conflict of Interests: Author
Comment: We updated the motifs and inculded the new analysis to predict the function of each SARS-CoV-2 protein based on the functional motifs found.
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