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Related Concept Videos

Protein-protein Interfaces02:04

Protein-protein Interfaces

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 polypeptide...
Protein-Protein Interfaces02:04

Protein-Protein Interfaces

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 polypeptide...
Protein Networks02:26

Protein Networks

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.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Protein Networks02:26

Protein Networks

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.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order to...
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order to...

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Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling
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A computational framework for boosting confidence in high-throughput protein-protein interaction datasets.

Raghavendra Hosur, Jian Peng, Arunachalam Vinayagam

    Genome Biology
    |September 4, 2012
    PubMed
    Summary

    We developed Coev2Net, a structure-based framework to improve protein interaction data quality. This method provides a single confidence score, outperforming existing approaches and aiding cancer research by identifying disease-related genetic variations.

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    Area of Science:

    • Biochemistry
    • Bioinformatics
    • Computational Biology

    Background:

    • High-throughput techniques for mapping protein interactions are crucial but suffer from uncertainty, impacting biomedical research.
    • Accurate protein interactome data is essential for understanding cellular mechanisms and disease pathways.

    Purpose of the Study:

    • To introduce Coev2Net, a novel structure-based framework for assessing the confidence of protein-protein interactions.
    • To develop a method that addresses both false-positive and false-negative rates in protein interaction data.
    • To provide a tool that enhances the quality and coverage of the protein interactome.

    Main Methods:

    • Coev2Net utilizes a structure-based approach to compute a single confidence score for binary protein interactions.
    • The framework is designed for scalability, applicable to thousands of protein interactions.
    • Experimental validation was performed on selected high-confidence predictions within the human MAPK network.

    Main Results:

    • Coev2Net demonstrates superior predictive performance compared to existing methods for evaluating protein interactions.
    • The framework successfully identifies protein interfaces enriched for cancer-related or damaging single nucleotide polymorphisms (SNPs).
    • Experimental validation confirmed the accuracy of high-confidence predictions in the human MAPK signaling pathway.

    Conclusions:

    • Coev2Net offers a robust and accurate method for improving the reliability of protein-protein interaction data.
    • The framework aids in identifying functionally significant protein interfaces, with implications for cancer research.
    • Coev2Net provides a valuable tool for researchers seeking to enhance the protein interactome map.