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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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Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key...
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Signal sequences are short amino acid sequences that guide newly synthesized proteins to their proper location within the cell. Classical signal sequences are fifteen to sixty amino acids long and present at the N-terminus of a polypeptide chain. Each signal sequence has a conserved segment of basic residues towards their N terminus, a hydrophobic core, and a C-terminus rich in polar residues. The C-terminus also contains a signal cleavage site and features a -3 -1 sequence motif. The -3-1...
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A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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Predicting Protein Relationships to Human Pathways through a Relational Learning Approach Based on Simple Sequence

Beatriz García-Jiménez, Tirso Pons, Araceli Sanchis

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |September 11, 2015
    PubMed
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    This study introduces a Relational Learning-based Extension (RLE) system to predict the functions of uncharacterized proteins by mapping them to biological pathways. The RLE system successfully associated hundreds of proteins to human Reactome pathways, aiding systems biology research.

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    Area of Science:

    • Systems biology
    • Bioinformatics
    • Computational biology

    Background:

    • Biological pathways are crucial for understanding complex cellular processes.
    • A significant portion of available genome-sequence data remains functionally uncharacterized.
    • Predicting the pathway membership of poorly annotated proteins is essential for systems biology.

    Purpose of the Study:

    • To develop a computational system for predicting the pathway membership of uncharacterized proteins.
    • To leverage protein properties and molecular similarities for function prediction.
    • To aid in the functional annotation of the human proteome.

    Main Methods:

    • Development of a Relational Learning-based Extension (RLE) system.
    • Utilizing combinations of simple protein properties for function prediction.
    • Searching for proteins with molecular similarities to known pathway components.

    Main Results:

    • Successfully associated 383 uncharacterized proteins to 28 human Reactome pathways.
    • Demonstrated relative confidence in predictions through evaluation.
    • Manual inspection and literature review supported proposed classifications for specific pathways.
    • Identified potential new components for pathways like Electron transport system, Telomere maintenance, and Integrin cell surface interactions.

    Conclusions:

    • The RLE system provides a reliable method for predicting protein function and pathway membership.
    • This approach aids in the functional characterization of unannotated proteins.
    • The findings contribute to a deeper understanding of biological pathways and systems biology.