Using molecular dynamics trajectories to predict nuclear spin relaxation behaviour in large spin systems.

Area of Science:

• Computational Chemistry
• Molecular Dynamics Simulations
• Nuclear Magnetic Resonance Spectroscopy

Background:

• Molecular dynamics (MD) simulations offer insights into molecular behavior, but their quantitative accuracy is debated.
• Experimental Nuclear Magnetic Resonance (NMR) spin relaxation rates can validate MD accuracy.
• Efficient computation of relaxation superoperators from MD trajectories is challenging due to the complexity of quantum Liouville space.

Purpose of the Study:

• To develop and report a computational module for efficiently calculating relaxation superoperators from MD trajectories.
• To enable quantitative validation of MD simulations using experimental NMR data.
• To assess the accuracy of MD-derived insights into molecular structure and dynamics.

Main Methods:

• Development of a module for the Spinach software framework.
• Computation of Bloch-Redfield-Wangsness relaxation superoperators, including non-secular terms and cross-correlations.
• Analysis of MD trajectories for sucrose using advanced water models and a glycan-optimized force field.

Main Results:

• The developed module efficiently computes relaxation superoperators from MD trajectories.
• Predicted initial slopes of nuclear Overhauser effects for sucrose were within 25% of experimental values.
• The study demonstrates the quantitative accuracy of MD insights when validated by NMR relaxation data.

Conclusions:

• The new module enhances the utility of MD trajectories for quantitative molecular analysis.
• MD simulations, when validated, provide reliable insights into molecular dynamics and structure.
• This work bridges the gap between computational predictions and experimental NMR measurements.