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Multi-parameter photon-by-photon hidden Markov modeling.

Paul David Harris1, Alessandra Narducci2, Christian Gebhardt2

  • 1Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Faculty of Mathematics & Science, The Edmond J. Safra Campus, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel. paul.harris@mail.huji.ac.il.

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|February 23, 2022
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Summary
This summary is machine-generated.

Multi-parameter hidden Markov modeling (mpH2MM) distinguishes biomolecular conformational changes from dye artifacts in single-molecule FRET studies. This method accurately quantifies dynamics across various timescales.

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Area of Science:

  • Biophysics
  • Structural Biology
  • Biochemistry

Background:

  • Single molecule Förster resonance energy transfer (smFRET) is a powerful technique for observing biomolecular conformational dynamics.
  • Photon-by-photon hidden Markov modeling (H2MM) analyzes smFRET data, but can be confounded by dye photophysical transitions.
  • Distinguishing true dynamics from artifacts is crucial for accurate interpretation of smFRET measurements.

Purpose of the Study:

  • To introduce multi-parameter H2MM (mpH2MM) for improved analysis of smFRET data.
  • To demonstrate mpH2MM's ability to decouple conformational dynamics from photophysical artifacts.
  • To validate mpH2MM across diverse biomolecular systems and timescales.

Main Methods:

  • Development and application of multi-parameter hidden Markov modeling (mpH2MM).
  • Confocal-based smFRET measurements of a DNA hairpin, maltose binding protein (MalE), and Yersinia YopO.
  • Analysis of conformational dynamics ranging from microsecond to sub-second timescales.

Main Results:

  • mpH2MM successfully identifies and quantifies FRET dynamics originating from conformational changes.
  • The method effectively distinguishes conformational dynamics from artifacts caused by dye photophysical transitions.
  • Validation across a DNA hairpin, MalE, and YopO demonstrates broad applicability.

Conclusions:

  • mpH2MM is a robust tool for accurate smFRET data analysis, overcoming limitations of standard H2MM.
  • This approach enables reliable identification and quantification of biomolecular sub-populations and their dynamics.
  • mpH2MM enhances the precision of biophysical studies on molecular conformational changes.