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Related Concept Videos

Protein Organization01:24

Protein Organization

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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.
The primary structure of a protein is its amino acid sequence....
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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
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Protein Structure Refinement Guided by Atomic Packing Frustration Analysis.

Mingchen Chen1, Xun Chen1,2, Shikai Jin1,3

  • 1Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005, United States.

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|September 15, 2020
PubMed
Summary
This summary is machine-generated.

Identifying packing frustration in predicted protein structures helps pinpoint errors. Guiding simulations with this atomic-level frustration analysis significantly improves structural accuracy and refinement efficiency.

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Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Machine learning in structural biology

Background:

  • Protein structure prediction has advanced with machine learning, but refinement remains challenging.
  • Unguided molecular dynamics simulations often fail to correct errors due to energy barriers.
  • Identifying and addressing incorrect contacts is crucial for accurate protein structure refinement.

Purpose of the Study:

  • To develop a method for localizing packing frustration at atomic resolution.
  • To assess the utility of atomic resolution frustration statistics for evaluating predicted protein structure quality.
  • To guide all-atom refinement simulations using atomic packing frustration analysis.

Main Methods:

  • Analyzing energetic changes upon local environment modification to identify packing frustration.
  • Calculating global statistics of atomic resolution frustration for predicted structures.
  • Using frustration analysis to guide all-atom refinement simulations.

Main Results:

  • Atomic resolution frustration effectively identifies locations of incorrect contacts in predicted protein structures.
  • Global frustration statistics serve as strong indicators of overall structural quality.
  • Minimally frustrated residues correlate with correctly positioned sites.
  • Refinement simulations guided by frustration analysis show significant quality improvements.

Conclusions:

  • Atomic packing frustration provides a powerful diagnostic tool for both global and local quality assessment of predicted protein structures.
  • Frustration-guided refinement is an efficient strategy for improving the accuracy of predicted protein models.
  • This approach enhances the reliability of protein structure prediction pipelines.