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Related Concept Videos

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

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Molecular Chaperones and Protein Folding03:00

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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.
The...
Molecular Chaperones and Protein Folding03:00

Molecular Chaperones and Protein Folding

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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Analysis of Protein Folding, Transport, and Degradation in Living Cells by Radioactive Pulse Chase
08:59

Analysis of Protein Folding, Transport, and Degradation in Living Cells by Radioactive Pulse Chase

Published on: February 12, 2019

Optimum folding pathways for growing protein chains.

Serife Senturk1, Sefer Baday, Yaman Arkun

  • 1College of Engineering, Koc University, Sariyer 34450 Istanbul, Turkey.

Physical Biology
|January 11, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a new method to simulate protein folding as chains grow residue by residue. This approach models the sequential addition of amino acids, predicting optimal folding pathways for proteins like villin headpiece and CI2.

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Last Updated: Jul 8, 2026

Analysis of Protein Folding, Transport, and Degradation in Living Cells by Radioactive Pulse Chase
08:59

Analysis of Protein Folding, Transport, and Degradation in Living Cells by Radioactive Pulse Chase

Published on: February 12, 2019

Microfluidic Mixers for Studying Protein Folding
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Published on: April 10, 2012

Assessment of Immunologically Relevant Dynamic Tertiary Structural Features of the HIV-1 V3 Loop Crown R2 Sequence by ab initio Folding
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Assessment of Immunologically Relevant Dynamic Tertiary Structural Features of the HIV-1 V3 Loop Crown R2 Sequence by ab initio Folding

Published on: September 15, 2010

Area of Science:

  • Biophysics
  • Computational Biology
  • Protein Science

Background:

  • Protein folding is crucial for biological function.
  • Understanding folding pathways is key to protein science.
  • Simulating protein folding dynamics presents computational challenges.

Purpose of the Study:

  • To develop a novel computational method for simulating protein folding.
  • To investigate protein folding as a chain grows sequentially from the N-terminus.
  • To predict optimal energy-minimizing folding pathways.

Main Methods:

  • A sequential dynamic optimization method was proposed.
  • The method utilizes Newton's equations of motion.
  • A Go-type potential was employed to model native contacts and excluded volume effects.

Main Results:

  • The folding of chicken villin headpiece (36 residues) was simulated, showing differences from prior refolding studies.
  • The folding of chymotrypsin inhibitor 2 (CI2, 64 residues) was simulated, largely agreeing with experimental and computational refolding data.
  • The method successfully predicts optimal energy-minimizing pathways for growing protein chains.

Conclusions:

  • The sequential dynamic optimization method provides a new perspective on protein folding dynamics.
  • This approach can accurately model folding pathways for various protein sizes.
  • The findings contribute to a deeper understanding of protein folding mechanisms.