Model-Free or Not?

Front Mol Biosci

Institute for Medical Physics and Biophysics, Medical Faculty, Leipzig University, Leipzig, Germany.

Published: October 2021

Relaxation in nuclear magnetic resonance is a powerful method for obtaining spatially resolved, timescale-specific dynamics information about molecular systems. However, dynamics in biomolecular systems are generally too complex to be fully characterized based on NMR data alone. This is a familiar problem, addressed by the Lipari-Szabo model-free analysis, a method that captures the full information content of NMR relaxation data in case all internal motion of a molecule in solution is sufficiently fast. We investigate model-free analysis, as well as several other approaches, and find that model-free, spectral density mapping, LeMaster's approach, and our analysis form a class of analysis methods, for which behavior of the fitted parameters has a well-defined relationship to the distribution of correlation times of motion, independent of the specific form of that distribution. In a sense, they are all "model-free." Of these methods, only detectors are generally applicable to solid-state NMR relaxation data. We further discuss how detectors may be used for comparison of experimental data to data extracted from molecular dynamics simulation, and how simulation may be used to extract details of the dynamics that are not accessible via NMR, where detector analysis can be used to connect those details to experiments. We expect that combined methodology can eventually provide enough insight into complex dynamics to provide highly accurate models of motion, thus lending deeper insight into the nature of biomolecular dynamics.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8573340PMC
http://dx.doi.org/10.3389/fmolb.2021.727553DOI Listing

Publication Analysis

Top Keywords

model-free analysis
8
nmr relaxation
8
relaxation data
8
dynamics
6
data
5
analysis
5
model-free
4
model-free not?
4
not? relaxation
4
relaxation nuclear
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!