From NMR relaxation to fractional Brownian dynamics in proteins: results from a virtual experiment

In a recent simulation study [J. Chem. Phys. 2010, 133, 145101], it has been shown that the time correlation functions probed by nuclear magnetic resonance (NMR) relaxation spectroscopy of proteins are well described by a fractional Brownian dynamics model, which accounts for the wide spectrum of relaxation rates characterizing their internal dynamics. Here, we perform numerical experiments to explore the possibility of using this model directly in the analysis of experimental NMR relaxation data. Starting from a molecular dynamics simulation of the 266 residue protein 6PGL in explicit water, we construct virtual (15)N R(1), R(2), and NOE relaxation rates at two different magnetic fields, including artificial noise, and test how far the parameters obtained from a fit of the model to the virtual experimental data coincide with those obtained from an analysis of the MD time correlation functions that have been used to construct these data. We show that in most cases, close agreement is found. Acceptance or rejection of parameter values obtained from relaxation rates are discussed on a physical basis, therefore avoiding overfitting.