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An Integrated Approach for Microprotein Identification and Sequence Analysis
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Computational Identification of Human Biological Processes and Protein Sequence Motifs Putatively Targeted by

Rachel Nadeau1,2,3, Soroush Shahryari Fard1,2,3, Amit Scheer1,2,3

  • 1Department of Biochemistry, Microbiology and Immunology, University of Ottawa, 451 Smyth Road, Ottawa, Ontario K1H 8M5, Canada.

Journal of Proteome Research
|October 26, 2020
PubMed

Insights

This study computationally analyzed SARS-CoV-2 interactions with human proteins to identify affected cellular processes and potential drug targets. Findings reveal key biological pathways and protein motifs involved in viral infection.

Area of Science:

  • Virology
  • Computational Biology
  • Molecular Biology

Background:

  • The COVID-19 pandemic, caused by SARS-CoV-2, has led to significant mortality, yet the virus's impact on human cells remains incompletely understood.
  • Investigating viral-host protein-protein interactions (PPIs) is crucial for elucidating viral mechanisms and identifying therapeutic targets.

Purpose of the Study:

  • To computationally analyze the SARS-CoV-2 human protein interactome.
  • To identify cellular processes and protein motifs potentially affected by SARS-CoV-2 infection.
  • To uncover potential therapeutic targets for COVID-19.

Main Methods:

  • Performed network-based functional and sequence motif enrichment analyses on viral-host PPI data from infected HEK 293 cells.
  • Utilized a novel implementation of the GoNet algorithm for Gene Ontology (GO) term enrichment.
  • Employed a new protein sequence motif discovery approach, LESMoN-Pro.

Main Results:

  • Identified 329 significantly enriched Gene Ontology terms associated with SARS-CoV-2-interacting human proteins within PPI networks.
  • Discovered 9 distinct amino acid motifs clustered in PPI networks, implicating them in SARS-CoV-2 infection.
  • Provided a comprehensive interactome analysis revealing virus-host cellular crosstalk.

Conclusions:

  • The study offers insights into cellular processes and protein motifs crucial for SARS-CoV-2 pathogenesis.
  • The identified pathways and motifs represent potential targets for novel antiviral therapies.
  • Computational interactome analysis is a valuable strategy for understanding viral infections and drug discovery.
Keywords:
COVID-19SARS-CoV-2clusteringenrichment analysisgene ontologygraph theorymotif discoveryprotein−protein interaction networkstatistics

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