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A computational protocol for 15N NMR parameter prediction in aqueous peptide ensembles using optimized DFT methods.

Minji Kim1, Jung Ho Lee1, Keunhong Jeong2

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Predicting nitrogen-15 NMR chemical shifts in flexible peptides is difficult. Our new computational method combining density functional theory and molecular dynamics improves prediction accuracy for peptide systems.

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Area of Science:

  • Computational chemistry
  • Nuclear Magnetic Resonance (NMR) spectroscopy
  • Biophysical chemistry

Background:

  • Accurate prediction of 15N NMR chemical shifts is crucial for understanding peptide structure and dynamics.
  • Flexible peptide systems present significant challenges for computational modeling due to their conformational heterogeneity.

Purpose of the Study:

  • To develop and validate an enhanced computational protocol for predicting 15N NMR chemical shifts in flexible peptide systems.
  • To improve the accuracy of NMR chemical shift predictions compared to traditional single-structure methods.

Main Methods:

  • An ensemble-based computational protocol was developed.
  • The protocol combines density functional theory (DFT) calculations with replica-exchange molecular dynamics (REMD) simulations.
  • The method was applied to a model peptide system.

Main Results:

  • The ensemble-based approach significantly outperformed single-structure predictions.
  • Average deviations for most residues were between 2.5-5.6 ppm.
  • A particularly accurate prediction with a deviation of 1.1 ppm was achieved for leucine residues.

Conclusions:

  • The presented computational protocol offers a substantial improvement for predicting 15N NMR chemical shifts in flexible peptides.
  • This method provides a more reliable tool for structural and dynamic studies of peptides using NMR spectroscopy.