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Related Concept Videos

Protein Networks02:26

Protein Networks

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,...
Protein Networks02:26

Protein Networks

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,...
Protein-protein Interfaces02:04

Protein-protein Interfaces

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 polypeptide...
Protein-Protein Interfaces02:04

Protein-Protein Interfaces

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 polypeptide...
Protein Folding01:22

Protein Folding

Overview
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.
Protein Structure Is Critical to Its Biological Function
Proteins perform a wide range of biological functions such as catalyzing chemical reactions, providing...

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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Network properties of protein-decoy structures.

Subhojyoti Chatterjee1, Moitrayee Bhattacharyya, Saraswathi Vishveshwara

  • 1Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.

Journal of Biomolecular Structure & Dynamics
|May 2, 2012
PubMed
Summary

Protein structure networks (PSNs) effectively distinguish native protein structures from decoys. Analyzing network parameters like cluster size and community structure aids in protein structure prediction and validation.

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Area of Science:

  • Structural biology
  • Computational biology
  • Biophysics

Background:

  • Protein folding converges to a limited conformational space, yet distinguishing native from non-native structures remains a challenge.
  • Existing methods for protein structure prediction and decoy discrimination include knowledge-based potentials and scoring functions based on surface area and amino acid neighborhoods.

Purpose of the Study:

  • To explore the potential of protein structure network (PSN) parameters for validating native protein structures against computationally generated decoys.
  • To assess if PSN parameters can serve as reliable metrics for identifying native structures and filtering out non-native ones.

Main Methods:

  • Constructed protein structure networks incorporating non-covalent interactions at the all-atom level, including side-chain atoms.
  • Analyzed network parameters such as the size of the largest cluster, community size, and clustering coefficient.
  • Scored network parameters based on the rank of native structures and Z-scores.

Main Results:

  • Network analysis revealed that global properties of protein structure networks contribute to the uniqueness of native protein structures.
  • The evaluated network parameters demonstrated effectiveness in identifying native structures and filtering out non-native decoys from large datasets.

Conclusions:

  • Protein structure network parameters can serve as valuable metrics for validating native protein structures.
  • This approach holds significant potential for improving the accuracy and efficiency of in silico protein structure prediction.