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Related Concept Videos

Protein Organization01:24

Protein Organization

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.
Protein Organization01:13

Protein Organization

Overview
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

VSEPR Theory for Determination of Electron Pair Geometries
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...
Protein Folding01:22

Protein Folding

Overview

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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

DANGLE: A Bayesian inferential method for predicting protein backbone dihedral angles and secondary structure.

Ming-Sin Cheung1, Mahon L Maguire, Tim J Stevens

  • 1Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK.

Journal of Magnetic Resonance (San Diego, Calif. : 1997)
|December 18, 2009
PubMed
Summary
This summary is machine-generated.

This study presents DANGLE, a new algorithm for protein structure analysis. DANGLE accurately predicts protein backbone dihedral angles using Bayesian inference and chemical shift data.

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Area of Science:

  • Biophysics
  • Structural Biology
  • Computational Biology

Background:

  • Protein structure determination is crucial for understanding function.
  • Nuclear magnetic resonance (NMR) chemical shifts provide valuable conformational information.
  • Predicting protein backbone dihedral angles (phi and psi) from chemical shifts remains challenging.

Purpose of the Study:

  • Introduce DANGLE, a novel algorithm for estimating protein backbone dihedral angles.
  • Leverage Bayesian inference and amino acid-specific conformational preferences.
  • Improve accuracy and coverage in dihedral angle prediction.

Main Methods:

  • Employ Bayesian inference to estimate probabilities of phi and psi angles for each residue.
  • Utilize observed chemical shifts and known amino acid conformational preferences.
  • Incorporate a degeneracy-based filtering procedure for enhanced accuracy.

Main Results:

  • DANGLE provides robust estimates of phi and psi angles within realistic ranges.
  • The method indicates degeneracy between shift measurements and conformation.
  • Achieves a favorable balance between accuracy and coverage compared to existing methods.
  • Identifies regions of residual structure in unfolded proteins.

Conclusions:

  • DANGLE offers a powerful new tool for protein dihedral angle prediction.
  • The analysis of shift/structure degeneracy aids in studying unfolded protein properties.
  • Demonstrates potential for identifying residual structures in denatured protein states.