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Related Concept Videos

Protein Networks02:26

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
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Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells
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Neglog: Homology-Based Negative Data Sampling Method for Genome-Scale Reconstruction of Human Protein-Protein

Suyu Mei1, Kun Zhang2

  • 1Software College, Shenyang Normal University, Shenyang 110034, China. meisygle@gmail.com.

International Journal of Molecular Sciences
|October 17, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces Neglog, a novel method to infer negative protein-protein interaction data, crucial for accurate computational models. Neglog enhances the reliability of protein-protein interaction network reconstruction by leveraging paralogous and orthologous relationships.

Keywords:
l2-regularized logistic regressionmachine learningnegative data samplingparalog/orthologprotein–protein interaction

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Systems Biology

Background:

  • Protein-protein interaction (PPI) networks are vital for understanding cellular functions and diseases.
  • Accurate computational modeling of PPIs is hindered by a scarcity of experimentally verified negative interaction data.

Purpose of the Study:

  • To develop a method for inferring reliable negative protein-protein interaction data.
  • To improve the accuracy and biological interpretability of computational models for PPI networks.

Main Methods:

  • The Neglog assumption: paralogs/orthologs of non-interacting proteins are also likely non-interacting.
  • Combined Neglog inference with random sampling for balanced training data construction.
  • Utilized L2-regularized logistic regression as the base classifier.

Main Results:

  • The Neglog method significantly outperforms random sampling in reconstructing PPI networks.
  • Demonstrated the biological interpretability of the Neglog approach.
  • Highlighted the importance of independent testing on negative data for bias control.

Conclusions:

  • Neglog provides a robust strategy for generating negative PPI data, addressing a key limitation in computational biology.
  • The method was successfully applied to validate PPIs in the STRING database, supported by Gene Ontology enrichment analyses.