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Related Experiment Videos

Quantifying polypeptide conformational space: sensitivity to conformation and ensemble definition.

David C Sullivan1, Carmay Lim

  • 1Institute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan. davidxyz1972@yahoo.com

The Journal of Physical Chemistry. B
|August 18, 2006
PubMed
Summary
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Quantifying protein conformational distributions is crucial for understanding protein folding. This study reveals that conformation counts vary widely based on ensemble and definition, impacting comparisons between models and simulations.

Area of Science:

  • Computational Biology
  • Biophysics
  • Protein Dynamics

Background:

  • Accurate quantification of conformational distributions is essential for modeling macromolecular processes like protein folding.
  • The cumulative distribution function (CDF) offers a method to analyze conformational space.

Purpose of the Study:

  • To quantify the conformational distribution of N-mer polyalanine using the CDF.
  • To investigate the sensitivity of conformation counts to ensemble definitions and conformational distance spans.
  • To assess the implications for comparing simplified models with all-atom molecular dynamics simulations.

Main Methods:

  • Utilized the cumulative distribution function (CDF) to quantify conformational distributions.
  • Analyzed N-mer polyalanine, specifically Ala(50), across different ensembles (random-walk, MD-relaxed).

Related Experiment Videos

  • Varied conformation definitions (1-2 Å root-mean-square-deviation radius) and solvent models (explicit waters).

    • Main Results:

    • Conformation counts for Ala(50) varied dramatically (10^11 to 10^69) based on ensemble and definition.
    • MD relaxation significantly reduced conformer counts (10^55 to 10^14) compared to random-walk ensembles.
    • Explicit waters were found to significantly alter the conformational landscape.

    Conclusions:

    • Conformation counts are highly sensitive to the chosen ensemble and definition, necessitating careful consideration when comparing studies.
    • Provides an upper limit for accessible conformations in unfolded protein states.
    • Offers guidance on optimal clustering radii and aids in assessing random search applicability in protein folding.
    • Highlights potential discrepancies between simplified unfolded protein models and all-atom MD simulations.