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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

Protein Folding

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Protein Folding01:22

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Amyloid Fibrils03:03

Amyloid Fibrils

Amyloid fibrils are aggregates of misfolded proteins.  Under most circumstances, misfolded proteins are either refolded by chaperone proteins or degraded by the proteasome. However, in the case of a mutation or a disease, these proteins can accumulate to form large clusters and often further assemble to form elongated fibers, called fibrils. 
Amyloid deposits were observed as early as 1639 in the liver and the spleen.   In 1854, Rudolph Virchow performed iodine staining, normally used to...
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.
The...
Protein Organization01:13

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Related Experiment Video

Updated: Jun 10, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

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Can peptide folding simulations provide predictive information for aggregation propensity?

Edmund I Lin1, M Scott Shell

  • 1Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California 93106-5080, USA.

The Journal of Physical Chemistry. B
|August 25, 2010
PubMed
Summary
This summary is machine-generated.

Nonnative peptide aggregation, a cause of disease and therapeutic challenge, is linked to molecular properties. Hydrophobic interactions are key drivers of this aggregation, as revealed by molecular dynamics simulations.

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Area of Science:

  • Biophysics
  • Computational Chemistry
  • Molecular Biology

Background:

  • Nonnative peptide aggregation is implicated in various diseases and poses challenges for peptide-based therapeutics.
  • Previous research identified correlations between peptide aggregation rates and simple sequence metrics like hydrophobicity and charge.

Purpose of the Study:

  • To investigate the relationship between molecular folding properties and peptide aggregation propensity.
  • To determine if molecular-level metrics can predict fibril formation and identify aggregation-prone regions.

Main Methods:

  • Utilized replica exchange molecular dynamics simulations to compute equilibrium conformational ensembles for 142 peptide systems.
  • Calculated various ensemble-based properties from simulation data.
  • Developed logistic regression models to predict fibril formation and assess the importance of molecular properties.

Main Results:

  • Identified molecular properties that correlate with peptide aggregation propensity.
  • Developed predictive models achieving 70-80% accuracy in identifying fibril-forming peptides.
  • Highlighted the dominant role of hydrophobic interactions in driving peptide aggregation.

Conclusions:

  • Molecular simulations provide insights into the driving forces of peptide aggregation.
  • Hydrophobic interactions are a primary factor in nonnative peptide aggregation.
  • Predictive models based on molecular properties can aid in the design of stable peptide therapeutics.