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Multi-schema computational prediction of the comprehensive SARS-CoV-2 vs. human interactome
Kevin Dick1,2, Anand Chopra3,4, Kyle K Biggar3,4
1Department of Systems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada.
Peerj
|April 19, 2021
Summary
This study mapped interactions between SARS-CoV-2 and human proteins to find therapeutic targets. The findings identify key protein-protein interactions (PPIs) for developing new COVID-19 treatments.
Area of Science:
- Virology
- Computational Biology
- Drug Discovery
Background:
- Understanding SARS-CoV-2 pathogenesis is crucial for developing effective therapeutics against COVID-19.
- Identifying SARS-CoV-2-human protein-protein interactions (PPIs) is key to finding therapeutic targets.
- A holistic view of the viral-human interactome aids in discovering inhibitory molecules.
Purpose of the Study:
- To generate a comprehensive SARS-CoV-2 vs. human interactome map.
- To identify high-confidence protein-protein interactions (PPIs) as potential therapeutic targets.
- To leverage computational tools for predicting and analyzing host-pathogen interactions.
Main Methods:
- Utilized PIPE4 and SPRINT, sequence-based PPI predictors, to generate the SARS-CoV-2 vs. human interactome.
- Employed three prediction schemas (all, proximal, RP-PPI) to refine high-confidence PPI identification.
- Applied the Reciprocal Perspective (RP) framework for improved predictive performance.
Main Results:
- Identified numerous high-confidence putative SARS-CoV-2-human PPIs across different schemas.
- The Spike-ACE2 interaction was consistently ranked highest, validating the prediction models.
- The PIPE-Sites algorithm identified interaction-mediating subsequences for potential therapeutic design.
Conclusions:
- A comprehensive dataset of SARS-CoV-2-human PPI predictions and PIPE-Sites landscapes has been publicly released.
- This resource aims to advance the scientific community's understanding of SARS-CoV-2.
- The data provides theoretical insights for developing novel anti-SARS-CoV-2 therapeutics.
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