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Related Experiment Video

Updated: Apr 28, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
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Increasing the precision of orthology-based complex prediction through network alignment.

Roland A Pache1, Patrick Aloy2

  • 1Joint IRB-BSC Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona) , Barcelona , Spain.

Peerj
|June 12, 2014
PubMed
Summary

Predicting protein complexes using computational methods and network alignment enhances accuracy. This study screened human, yeast, and fly interactomes, identifying conserved and novel complexes, and revealing therapeutic targets in Mycoplasma pneumoniae.

Keywords:
Complex predictionEvolutionary conservationMacromolecular assembliesNetwork alignmentProtein complexesProtein–protein interactions

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Area of Science:

  • * Computational biology
  • * Molecular systems biology
  • * Bioinformatics

Background:

  • * Macromolecular assemblies are crucial for cellular functions, but knowledge of protein complex composition remains limited.
  • * In silico prediction methods are essential for expanding our understanding of complex organization in model organisms.
  • * Protein-protein interactions constrain functional divergence, enabling orthology-based complex prediction.

Purpose of the Study:

  • * To improve the precision of orthology-based protein complex prediction by integrating interaction data via network alignment.
  • * To conduct a large-scale in silico screen for protein complexes in human, yeast, and fly.
  • * To identify conserved and novel protein complexes and assess their functional roles.

Main Methods:

  • * Network alignment of known complexes to whole-organism interactomes.
  • * In silico screening across human, yeast, and fly proteomes.
  • * Orthogonal data validation and functional role assignment for predicted complexes.
  • * Comparative analysis of protein complex repertoires, including the pathogen Mycoplasma pneumoniae.

Main Results:

  • * Integrating interaction data via network alignment significantly enhances the precision of complex prediction.
  • * A large-scale screen identified numerous conserved and novel protein complexes in human, yeast, and fly.
  • * Predicted complexes were validated and assigned specific functional roles.
  • * Yeast protein complex knowledge is more extensive than in other organisms; fly complex prediction is complementary.
  • * Mycoplasma pneumoniae exhibits a distinct protein complex repertoire compared to eukaryotes, offering potential therapeutic targets.

Conclusions:

  • * Network alignment is a powerful tool for accurate in silico prediction of protein complexes.
  • * The study provides a valuable resource of predicted complexes for human, yeast, and fly.
  • * Comparative analysis highlights evolutionary conservation and species-specific differences in complex organization.
  • * Findings in Mycoplasma pneumoniae suggest novel therapeutic strategies and potential host-pathogen interactions.