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Predicting Interacting Protein Pairs by Coevolutionary Paralog Matching.

Thomas Gueudré1, Carlo Baldassi2,3, Andrea Pagnani1,3,4

  • 1Italian Institute for Genomic Medicine, Turin, Italy.

Methods in Molecular Biology (Clifton, N.J.)
|October 5, 2019
PubMed
Summary

Identifying specific interacting protein paralogs within families is challenging. Our new coevolutionary analysis tool accurately predicts these interactions, even when other methods fail.

Keywords:
CoevolutionDirect coupling analysisParalog matchingPredicting interacting paralogsProtein–protein interaction

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Area of Science:

  • Biochemistry
  • Bioinformatics
  • Computational Biology

Background:

  • Protein families often contain multiple homologous sequences (paralogs) within a species.
  • Determining specific paralog interactions within interacting protein families remains a significant challenge in molecular biology.

Purpose of the Study:

  • To develop and present an efficient computational tool for predicting interacting protein paralogs between two protein families.
  • To address limitations of existing methods like genomic co-localization and orthology-based approaches.

Main Methods:

  • The developed tool utilizes the principle of inter-protein coevolution.
  • It identifies and matches paralogs from the same species that collectively maximize the coevolutionary signal.
  • The method is implemented using freely available software for accessibility.

Main Results:

  • The algorithm successfully predicts interacting paralogs where simpler methods fail.
  • Demonstrates applicability across diverse protein families and species.
  • Provides an efficient implementation for practical use in biological research.

Conclusions:

  • The novel coevolution-based approach offers a robust solution for identifying specific protein paralog interactions.
  • This tool enhances our understanding of protein-protein interaction networks at a finer resolution.
  • Facilitates further research in functional genomics and systems biology.