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Protein Organization01:24

Protein Organization

10.2K
Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....
10.2K
Protein-protein Interfaces02:04

Protein-protein Interfaces

15.1K
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...
15.1K
Protein-Protein Interfaces02:04

Protein-Protein Interfaces

4.6K
4.6K
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,...
4.7K
Protein Networks02:26

Protein Networks

3.0K
3.0K
Conserved Binding Sites01:49

Conserved Binding Sites

5.3K
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...
5.3K

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Related Experiment Video

Updated: Apr 19, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

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Adjusting protein graphs based on graph entropy.

Sheng-Lung Peng, Yu-Wei Tsay

    BMC Bioinformatics
    |December 5, 2014
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces graph entropy as a novel method to assess protein graph suitability for structural comparison. This approach enhances protein graph modeling and aids in determining structural similarity.

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    A Protocol for Computer-Based Protein Structure and Function Prediction

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    Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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    A Protocol for Computer-Based Protein Structure and Function Prediction
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    A Protocol for Computer-Based Protein Structure and Function Prediction

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    Area of Science:

    • Computational Biology
    • Graph Theory
    • Structural Bioinformatics

    Background:

    • Protein structural similarity is crucial for understanding biological function.
    • Traditional methods often rely on pairwise superimposition, which can be computationally intensive.
    • Recent research explores protein graph remodeling as an alternative approach.

    Purpose of the Study:

    • To propose a novel measurement for protein graph remodeling based on graph entropy.
    • To establish a criterion for verifying the structural stability of protein graphs.
    • To enhance the suitability of protein graphs for structural comparison.

    Main Methods:

    • Representing proteins as graphs.
    • Extending the concept of graph entropy to protein graphs.
    • Developing a graph entropy-based criterion for graph suitability.

    Main Results:

    • Graph entropy effectively measures the suitability of a graph for representing a protein.
    • The proposed method aids in protein graph modeling and conformational analysis.
    • Experimental results indicate graph entropy's utility in assessing protein graph stability.

    Conclusions:

    • Graph entropy provides a robust criterion for evaluating protein graphs.
    • This method indirectly contributes to more reliable protein structural comparison.
    • The approach offers an efficient alternative for analyzing protein structures.