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Related Concept Videos

Protein Networks02:26

Protein Networks

4.7K
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,...
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Protein-protein Interfaces02:04

Protein-protein Interfaces

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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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Conserved Binding Sites01:49

Conserved Binding Sites

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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.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
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Related Experiment Video

Updated: Apr 6, 2026

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling
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Node sampling for protein complex estimation in bait-prey graphs.

Denise M Scholtens, Bruce D Spencer

    Statistical Applications in Genetics and Molecular Biology
    |July 31, 2015
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a stratified sampling method for protein complex analysis using co-immunoprecipitation (CoIP). This approach improves the accuracy of protein network estimations compared to random sampling, optimizing experimental design.

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    Area of Science:

    • Cellular Biology
    • Systems Biology
    • Bioinformatics

    Background:

    • Protein-protein interactions form complex networks crucial for cellular functions.
    • Co-immunoprecipitation (CoIP) is a key technology for assaying protein complex membership.
    • Budgetary constraints often limit comprehensive network analysis via CoIP.

    Purpose of the Study:

    • To develop an efficient sampling strategy for CoIP experiments focused on protein complex estimation.
    • To enhance the accuracy and yield of correctly identified protein complexes.
    • To provide a data-driven method for selecting baits in network studies.

    Main Methods:

    • A stratified sampling scheme is proposed, defining generalized nodes as strata based on adjacency.
    • Strata are dynamically redefined in each sampling round to incorporate new data.
    • The scheme aims to maintain user-specified quality thresholds for complex estimates.

    Main Results:

    • The stratified sampling scheme significantly increases the number of correctly estimated protein complexes per sampling round.
    • This method outperforms simple random sampling in accuracy and efficiency.
    • The R package 'seqSample' implements the described methodology.

    Conclusions:

    • Stratified sampling offers a more effective approach to protein complex estimation in large biological networks.
    • This method optimizes resource allocation in CoIP experiments.
    • The 'seqSample' package facilitates the application of this advanced sampling technique.