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Related Concept Videos

Protein Networks02:26

Protein Networks

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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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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.
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Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry
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Identifying conserved protein complexes between species by constructing interolog networks.

Phi-Vu Nguyen, Sriganesh Srihari, Hon Wai Leong

    BMC Bioinformatics
    |February 26, 2014
    PubMed
    Summary
    This summary is machine-generated.

    We developed a new method to identify conserved protein complexes between species by integrating domain and sequence conservation. This approach significantly improves accuracy and reveals complex evolutionary changes, aiding in understanding core cellular machinery and potential therapeutic targets.

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    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Systems Biology

    Background:

    • Protein complexes are crucial for core cellular functions and conserved across species.
    • Existing methods for identifying protein complexes from protein-interaction networks (PPIs) suffer from noise and false positives.
    • Many conserved complexes, like the MLH1-MSH2-PMS2-PCNA mismatch-repair complex, are missed by current computational approaches.

    Purpose of the Study:

    • To develop a novel computational method for identifying conserved protein complexes between species.
    • To leverage domain conservation in addition to sequence similarity for improved complex detection.
    • To address limitations of existing methods in handling noisy PPI data and identify missed conserved complexes.

    Main Methods:

    • Constructed an interolog network (IN) by integrating domain conservation (from Ensembl) and sequence similarity.
    • Applied state-of-the-art clustering methods to the interolog network.
    • Mapped identified clusters back to original PPI networks to pinpoint conserved complexes.
    • Evaluated the COCIN (Complex Of Conserved Interacting Networks) approach using human and yeast interaction data.

    Main Results:

    • The IN-based COCIN approach achieved 76% recall in identifying conserved complexes, significantly outperforming direct detection from PPIs (54% recall).
    • Interolog network construction effectively removed non-conserved interactions, many of which were false positives, thereby enhancing complex prediction accuracy.
    • Identified key conserved complexes including mismatch repair (MLH1-MSH2-PMS2-PCNA), RNA polymerase-II, EIF3, and MCM complexes, vital for core cellular processes.
    • Demonstrated that removing non-conserved interactions from original PPIs also improved conserved complex identification, validating the IN-based strategy.

    Conclusions:

    • Integrating domain and sequence conservation to build interolog networks is a powerful strategy for identifying conserved protein complexes across species.
    • Protein complex conservation between species is not a simple subset relationship but involves significant evolutionary reorganization and functional redistribution.
    • These findings have implications for understanding complex evolution and for extrapolating biological relationships, such as synthetic lethality, between species for applications like cancer target identification.