Abstract
Nuclear magnetic resonance (NMR) spin relaxation is the most informative approach to experimentally probe the internal dynamics of proteins on the picosecond to
nanosecond timescale. At the same time, molecular dynamics (MD) simulations of biological macromolecules are steadily improving through better physical models, enhanced sampling algorithms, and increasing computational power, and they provide exquisite
information about flexibility and its role in protein stability and molecular interactions. Many examples have shown that MD is now adept in probing protein backbone motion,
but improvements are still required towards a quantitative description of the dynamics of side chains, for example probed by the dynamics of methyl groups. Thus far, the comparison of computation with experiment for side chains has primarily focused on the relaxation of 13C and 2H nuclei induced by auto-correlated variation of spin
interactions. However, the cross-correlation of 13C-1H dipolar interactions in methyl groups offers an attractive alternative. Here, we establish a methodological framework
to extract cross-correlation relaxation parameters of methyl groups in proteins from all-atom MD simulations. To demonstrate the utility of the approach, cross-correlation
relaxation rates of ubiquitin are computed from MD simulations performed with the AMBER99SB*-ILDN and CHARMM36 force fields. The simulation results were found
to agree well with those obtained by experiment. Moreover, the data obtained with the two force fields are highly consistent.