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

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.