Validation of the GROMOS force-field parameter set 45Alpha3 against nuclear magnetic resonance data of hen egg...

The quality of molecular dynamics (MD) simulations of proteins depends critically on the biomolecular force field that is used. Such force fields are defined by force-field parameter sets, which are generally determined and improved through calibration of properties of small molecules against experimental or theoretical data. By application to large molecules such as proteins, a new force-field parameter set can be validated. We report two 3.5 ns molecular dynamics simulations of hen egg white lysozyme in water applying the widely used GROMOS force-field parameter set 43Alpha1 and a new set 45Alpha3. The two MD ensembles are evaluated against NMR spectroscopic data NOE atom-atom distance bounds, (3)J(NHalpha) and (3)J(alphabeta) coupling constants, and (15)N relaxation data. It is shown that the two sets reproduce structural properties about equally well. The 45Alpha3 ensemble fulfills the atom-atom distance bounds derived from NMR spectroscopy slightly less well than the 43Alpha1 ensemble, with most of the NOE distance violations in both ensembles involving residues located in loops or flexible regions of the protein. Convergence patterns are very similar in both simulations atom-positional root-mean-square differences (RMSD) with respect to the X-ray and NMR model structures and NOE inter-proton distances converge within 1.0-1.5 ns while backbone (3)J(HNalpha)-coupling constants and (1)H-(15)N order parameters take slightly longer, 1.0-2.0 ns. As expected, side-chain (3)J(alphabeta)-coupling constants and (1)H-(15)N order parameters do not reach full convergence for all residues in the time period simulated. This is particularly noticeable for side chains which display rare structural transitions. When comparing each simulation trajectory with an older and a newer set of experimental NOE data on lysozyme, it is found that the newer, larger, set of experimental data agrees as well with each of the simulations. In other words, the experimental data converged towards the theoretical result.