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Related Concept Videos

Protein Networks02:26

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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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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.
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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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A Protocol for Computer-Based Protein Structure and Function Prediction
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FlexE: Using elastic network models to compare models of protein structure.

Alberto Perez1, Zheng Yang2, Ivet Bahar2

  • 1Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794-5252.

Journal of Chemical Theory and Computation
|December 23, 2014
PubMed
Summary

We introduce FlexE, a novel method for protein structure comparison. FlexE uses deformation energy from an elastic network model to assess similarity, capturing flexibility beyond fixed geometry methods.

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Area of Science:

  • Biophysics
  • Structural Biology
  • Computational Biology

Background:

  • Protein structure comparison is crucial for understanding biological function.
  • Existing methods like RMSD and GDT-TS rely on fixed geometry, neglecting protein flexibility.
  • This limitation hinders the accurate assessment of biologically relevant conformational changes.

Purpose of the Study:

  • To develop a novel method, FlexE, for protein structure comparison.
  • To incorporate protein flexibility and energy landscape into structural similarity assessment.
  • To differentiate between biologically significant and random structural variations.

Main Methods:

  • FlexE utilizes a simple elastic network model.
  • Deformation energy is calculated as the primary measure of structural similarity.
  • The method integrates the concept of thermal energy for defining structural equivalence.

Main Results:

  • FlexE successfully distinguishes biologically relevant conformational changes from random fluctuations.
  • The method provides a measure of similarity that accounts for intrinsic protein flexibility.
  • FlexE offers a rational approach to determine when two protein models are conformationally equivalent.

Conclusions:

  • FlexE offers a complementary approach to existing geometry-based protein structure comparison methods.
  • The method's ability to capture flexibility enhances the biological relevance of structural comparisons.
  • FlexE provides a unique and valuable metric for assessing protein structural similarity.