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Related Concept Videos

Protein Folding01:22

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Protein Folding01:25

Protein Folding

Proteins are chains of amino acids linked together by peptide bonds. Upon synthesis, a protein folds into a three-dimensional conformation, critical to its biological function. Interactions between its constituent amino acids guide protein folding, and hence the protein structure is primarily dependent on its amino acid sequence.
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Proteins perform a wide range of biological functions such as catalyzing chemical reactions, providing...
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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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The primary structure of a protein is its amino acid sequence.

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A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Protein pockets: inventory, shape, and comparison.

Ryan G Coleman1, Kim A Sharp

  • 1Department of Biochemistry and Biophysics, The Johnson Research Foundation, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.

Journal of Chemical Information and Modeling
|March 9, 2010
PubMed
Summary
This summary is machine-generated.

CLIPPERS provides a novel method for identifying and analyzing protein pockets. This complete inventory of protein pockets (CLIPPERS) method offers a hierarchical tree of pockets, enabling quantitative comparisons and detailed shape analysis.

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Last Updated: Jun 15, 2026

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Area of Science:

  • Structural Biology
  • Computational Biology
  • Biochemistry

Background:

  • Protein surface shape determines macromolecular interactions.
  • Defining and comparing protein pockets (binding sites) is challenging.
  • Existing methods struggle with pocket extent, characterization, and quantitative comparison.

Purpose of the Study:

  • To develop a comprehensive method for identifying and analyzing protein pockets.
  • To enable quantitative comparisons of pockets across different proteins.
  • To facilitate analysis of pocket changes in evolutionary or time-dependent series.

Main Methods:

  • A novel algorithm, CLIPPERS (complete liberal inventory of protein pockets elucidating and reporting on shape), was developed.
  • Surface and solvent points are sorted by travel depth to create a hierarchical tree of pockets.
  • Pocket connectivity is determined by saddle points; shape metrics (volume, surface area, mouth size) are computed.
  • Pockets are annotated with lining residues and other properties.

Main Results:

  • CLIPPERS generates a complete inventory of protein pockets, tessellating the entire protein surface.
  • The method allows for easy computation of key pocket shape metrics.
  • A hierarchical structure facilitates pocket merging, grouping, filtering, and visualization.
  • Quantitative pocket comparison is achieved using shape metrics, avoiding complex shape alignment.

Conclusions:

  • CLIPPERS offers a robust solution for identifying, characterizing, and comparing protein pockets.
  • The method guarantees finding all pockets, unlike previous approaches.
  • It aids in analyzing pocket dynamics, evolutionary changes, and ligand binding site alterations.