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Force field optimization using dynamics and ensemble averaged data: vibrational spectra and relaxation in bound MbCO.

Michael Devereux1, Markus Meuwly

  • 1Department of Chemistry, University of Basel, Klingelbergstrasse 80, Basel, Switzerland.

Journal of Chemical Information and Modeling
|February 12, 2010
PubMed
Summary

Optimizing force field parameters using molecular dynamics (MD) simulations improves atomistic simulations. This approach accurately predicts vibrational frequencies and relaxation times for carbon monoxide-bound myoglobin (MbCO).

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Area of Science:

  • Computational Chemistry
  • Biophysics
  • Molecular Dynamics

Background:

  • Force field parameters are crucial for accurate atomistic simulations.
  • Optimizing these parameters often involves fitting to experimental data or theoretical calculations.
  • Understanding vibrational dynamics in metalloproteins like myoglobin is essential for studying their function.

Purpose of the Study:

  • To investigate the impact of incorporating averaged data from explicit molecular dynamics (MD) simulations into the optimization of potential energy functions.
  • To develop and validate a single set of force field parameters for accurately representing vibrational frequencies and relaxation times in carbon monoxide-bound myoglobin (MbCO).
  • To assess the transferability of parameters fitted to a subsystem of MbCO to the full protein system.

Main Methods:

  • Optimization of potential energy functions using averaged data from explicit MD simulations.
  • Fitting force field parameters to vibrational frequencies (Fe-C, C-O stretch, Fe-C-O bend) and CO vibrational relaxation times (T(10), T(21)) in MbCO.
  • Testing parameter transferability from a MbCO subsystem (CO ligand, heme, proximal histidine) to the full protein.

Main Results:

  • A single set of force field parameters accurately represents vibrational frequencies and CO vibrational relaxation times in MbCO.
  • Parameters fitted to a subsystem are transferable to the full protein, yielding quantitatively correct results.
  • Calculated frequencies are within ~5% of experimental values; T(10) is ~25 ps (experimental ~17 ps) with quantum corrections; T(10)/T(21) ratio is ~2, matching experimental estimates.
  • Traditional Hessian matrix-based fitting captures frequencies but not vibrational relaxation.

Conclusions:

  • Including averaged MD simulation data in force field optimization is a viable strategy for improving atomistic simulations.
  • The developed force field parameters provide accurate predictions of both vibrational frequencies and relaxation dynamics in MbCO.
  • Parameter transferability from subsystems to larger systems is demonstrated, offering a more efficient approach to force field development.