Molecular
simulations with seven current AMBER- and CHARMM-based
force fields yield markedly differing internal bond vector autocorrelation
function predictions for many of the 223 methine and methylene H–C
bonds of the 56-residue protein GB3. To enable quantification of accuracy, 13C R1, R2, and heteronuclear NOE relaxation
rates have been determined for the methine and stereochemically assigned
methylene Cα and Cβ positions. With
only three experimental relaxation values for each bond vector, central
to this analysis is the accuracy with which MD-derived autocorrelation
curves can be represented by a 3-parameter equation which, in turn,
maps onto the NMR relaxation values. In contrast to the more widely
used extended Lipari-Szabo order parameter representation, 95% of
these MD-derived internal autocorrelation curves for GB3 can be fitted
to within 1.0% rmsd over the time frame from 30 ps to 4 ns by a biexponential
Larmor frequency-selective representation (LF-S2). Applying
the LF-S2 representation to the experimental relaxation
rates and uncertainties serves to determine the boundary range for
the autocorrelation function of each bond vector consistent with the
experimental data. Not surprisingly, all seven force fields predict
the autocorrelation functions for the more motionally restricted 1Hα–13Cα and 1Hβ–13Cβ bond vectors with reasonable accuracy. However, for the 1Hβ–13Cβ bond
vectors exhibiting aggregate order parameter S2 values
less than 0.85, only 1% of the MD-derived predictions lie with 1 σ
of the experimentally determined autocorrelation functions and only
7% within 2 σ. On the other hand, substantial residue type-specific
improvements in predictive performance were observed among the recent
AMBER force fields. This analysis indicates considerable potential
for the use of 13C relaxation measurements in guiding the
optimization of the side chain dynamics characteristics of protein
molecular simulations.