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Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
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Persistent Protein Motions in a Rugged Energy Landscape Revealed by Normal Mode Ensemble Analysis.

Tod D Romo1, Alan Grossfield1, Andrea G Markelz2

  • 1Department of Biochemistry and Biophysics, University of Rochester Medical Center, Rochester, New York 14642, United States.

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Summary
This summary is machine-generated.

Identifying protein vibrations linked to function is challenging. New methods reveal these crucial, narrow frequency bands by analyzing protein dynamics and anisotropic absorption spectra.

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Area of Science:

  • Biophysics
  • Computational Biology
  • Structural Biology

Background:

  • Proteins utilize allosteric mechanisms, involving motions at distant sites, to regulate biological functions.
  • Low-frequency structural vibrations are proposed as a key mechanism for this long-distance communication.
  • Experimentally identifying specific functional vibrations has been a significant challenge, despite spectroscopy's potential.

Purpose of the Study:

  • To address the challenge of experimentally identifying protein structural vibrations associated with specific functional motions.
  • To investigate methods for robustly characterizing protein vibrations and overcoming spectral congestion.
  • To reconcile computational predictions with experimental observations regarding protein dynamics.

Main Methods:

  • Utilized an aggregate of 18.5 μs all-atom molecular dynamics simulations of hen egg white lysozyme.
  • Applied normal mode analyses to explore protein structural vibrations across the sampled energy landscape.
  • Analyzed ensemble-averaged anisotropic absorption spectra, alongside vibrational density of states and isotropic absorption.

Main Results:

  • Found that functional displacements correlate with vibrations concentrated in narrow frequency bands.
  • Observed that these functional bands are obscured in ensemble-averaged vibrational density of states and isotropic absorption.
  • Demonstrated persistent spectral structure in ensemble-averaged anisotropic absorption, overlapping with functional frequency bands.

Conclusions:

  • Protein energy landscape sampling and statistical analysis are crucial for robust spectral characterization.
  • Ensemble-averaged anisotropic absorption, combined with normal mode analysis, can reveal hidden functional vibration bands.
  • This integrated approach overcomes spectral congestion, enabling identification of functionally relevant protein vibrations.