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Quantitative single-molecule conformational distributions: a case study with poly-(L-proline).

Lucas P Watkins1, Hauyee Chang, Haw Yang

  • 1Department of Chemistry, University of California at Berkeley, and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA.

The Journal of Physical Chemistry. A
|April 14, 2006
PubMed
Summary
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A new method accurately determines molecular conformational distributions using constant-information analysis and maximum entropy deconvolution. This technique reveals static end-to-end distances in poly(L-proline) chains, applicable across various lengths.

Area of Science:

  • Biophysics
  • Polymer Science
  • Physical Chemistry

Background:

  • Understanding biological macromolecule dynamics and reactivity requires precise potential of mean force measurements.
  • Single-molecule fluorescence measurements offer unique insights into molecular behavior.

Purpose of the Study:

  • To develop an accurate method for determining molecular conformational distributions using single-molecule fluorescence data.
  • To derive analytical expressions for errors in conformational distribution determination.
  • To apply the developed method to poly(L-proline) chains and compare experimental results with theoretical models.

Main Methods:

  • Utilized a constant-information approach with maximum entropy deconvolution for analyzing time-dependent single-molecule fluorescence data.

Related Experiment Videos

  • Employed a modular, server-based single-molecule spectrometer with continuous-wave excitation.
  • Calibrated and corrected for background, cross-talk, and detection efficiency for each molecule.

    • Main Results:

    • Achieved accurate determination of molecular conformational distributions for poly(L-proline) series P(n)CG3K(biotin).
    • Recovered sharply peaked Förster type resonance energy transfer (FRET) efficiency and distance distributions, indicating static end-to-end distances.
    • Experimental distances were consistent with a 23 angstroms persistence length wormlike chain model.

    Conclusions:

    • The developed constant-information approach provides accurate molecular conformational distributions and error analysis.
    • The findings suggest that the wormlike chain model with a 23 angstroms persistence length is applicable to both short and high molecular weight poly(L-proline) chains.