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Inter-species validation for domain combination based protein-protein interaction prediction method.

Woo-Hyuk Jang1, Dong-Soo Han, Hong-Soog Kim

  • 1School of Engineering, Information and Communications University, 119, Munjiro, Daejeon, 305-714, Korea. torajim@icu.ac.kr

Genome Informatics. International Conference on Genome Informatics
|August 12, 2006
PubMed
Summary

The Domain Combination based Protein-Protein Interaction Prediction (DCPPIP) method accurately predicts protein interactions in flies and humans. Its effectiveness extends across species, correlating with domain similarity.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • The Domain Combination based Protein-Protein Interaction Prediction (DCPPIP) method demonstrated high accuracy for yeast proteins.
  • The applicability and accuracy of DCPPIP for proteins in other species remained unverified.
  • Cross-species validation is crucial for understanding the generalizability of prediction methods.

Purpose of the Study:

  • To validate the DCPPIP method for predicting protein-protein interactions in Drosophila melanogaster (Fly) and Homo sapiens (Human).
  • To assess the performance of DCPPIP in inter-species prediction scenarios.
  • To investigate the relationship between domain similarity and prediction accuracy across species.

Main Methods:

  • Applied the DCPPIP method to predict interactions for Fly (10,351 pairs) and Human (2,345 pairs) datasets, using 80% for training and 20% for testing.

Related Experiment Videos

  • Conducted inter-species validation using protein interaction and domain data from Yeast, Fly, and combined Yeast-Fly as learning sets for predicting interactions in Human, Mouse, H. pylori, E. coli, and C. elegans.
  • Introduced and analyzed the Domain Overlapping Rate (DOR) to quantify domain similarity between species.

    • Main Results:

    • Achieved high prediction accuracies for Fly (sensitivity ~77%, specificity ~92%) and Human (sensitivity ~96%, specificity ~95%).
    • Demonstrated good prediction accuracy in inter-species validation, particularly when test proteins shared common domains with learning set proteins.
    • Identified a clear correlation between the developed Domain Overlapping Rate (DOR) and prediction accuracy across different species.

    Conclusions:

    • The DCPPIP method is effective and accurate for predicting protein-protein interactions in both Fly and Human proteomes.
    • DCPPIP shows robust performance in inter-species prediction, highlighting its potential for broader applications.
    • Domain similarity, quantified by DOR, is a significant factor influencing the accuracy of cross-species protein-protein interaction prediction.