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Related Concept Videos

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.
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Proteins perform a wide range of biological functions such as catalyzing chemical reactions, providing...
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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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The native conformation of a protein is formed by interactions between the side chains of its constituent amino acids. When the amino acids cannot form these interactions, the protein cannot fold by itself and needs chaperones. Notably, chaperones do not relay any additional information required for the folding of polypeptides; the native conformation of a protein is determined solely by its amino acid sequence. Chaperones catalyze protein folding without being a part of the folded protein.
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Related Experiment Video

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Single-Molecule Measurement of Protein Interaction Dynamics Within Biomolecular Condensates
06:48

Single-Molecule Measurement of Protein Interaction Dynamics Within Biomolecular Condensates

Published on: January 5, 2024

Quantifying hub-like behavior in protein folding networks.

Alex Dickson1, Charles L Brooks

  • 1Department of Chemistry, The University of Michigan, Ann Arbor, MI, and Department of Chemistry and Biophysics Program, The University of Michigan, Ann Arbor, MI.

Journal of Chemical Theory and Computation
|September 13, 2013
PubMed
Summary

We developed a new metric to analyze protein folding pathways. This metric quantifies the connectivity of unfolded states, distinguishing between funnel-like and hub-like protein folding landscapes.

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Area of Science:

  • Biophysics
  • Computational Biology
  • Protein Dynamics

Background:

  • Protein folding landscapes are complex, visualized using concepts like funnels.
  • A hub-like native state model proposes multiple folding pathways converging on the native state.
  • This contrasts with models featuring a single pathway to a rapidly interconverting unfolded ensemble.

Purpose of the Study:

  • To introduce a novel metric for quantifying the connectivity of the unfolded ensemble in protein folding.
  • To differentiate between hub-like and funnel-like protein folding landscapes.
  • To assess the role of the native state in mediating transitions within the unfolded ensemble.

Main Methods:

  • Development of a network-based metric to determine the connectivity of the unfolded ensemble.
  • Calculation of the metric using continuous folding trajectories.
  • Calculation of the metric using a Markov model.

Main Results:

  • The metric quantifies the frequency with which regions of conformational space are used as intermediates in transition paths.
  • The study assesses the direct connectivity between different parts of the unfolded ensemble.
  • It evaluates the extent to which transitions are mediated by the native state.

Conclusions:

  • The developed metric provides a quantitative approach to characterize protein folding landscapes.
  • It allows for the distinction between different models of protein folding, specifically hub-like versus funnel-like.
  • This metric aids in understanding the complex dynamics and pathways governing protein folding.