Comparison of NMR and MD N–H bond order parameters: example of HIV-1 protease

Starting-Condition Dependence of Order Parameters Derived from Molecular Dynamics Simulations

We have studied how backbone N-H S(2) order parameters calculated from molecular dynamics simulations depend on the method used to calculate them, the starting conditions, and the length of the simulations. Using the carbohydrate binding domain of galectin-3 in the free and lactose-bound states as a test case, we compared the calculated order parameters with experimental data from NMR relaxation. The results indicate that the sampling can be improved by using several starting structures, taking into account conformational heterogeneity reported in crystal structures. However, the improvement is rather limited, and for 93% of the dihedrals that have alternative conformations in the crystal structures, the conformational space is well sampled even if a single conformation is used as the starting structure. Moreover, the agreement with experimental data is improved when using several short simulations, rather than a single long simulation. In the present case, we find that ∼10 independent simulations provide sufficient sampling, and the ideal length of the simulations is ∼10 ns, which is ∼25% longer than the global correlation time for rotational diffusion. On the other hand, the equilibration time appears to be less important, and our results suggest that an equilibration time of 0.25 ns is sufficient. We have also compared four different methods to extract the order parameters from the simulations, namely, the autocorrelation function and isotropic reorientational eigenmode dynamics using three different window sizes. Overall, the four methods yield comparable results, but large differences between the methods may serve to pinpoint cases for which the calculated parameters are unreliable.

Multiple molecular dynamics simulation of the isoforms of human translation elongation factor 1A reveals reversible fluctuations between "open" and "closed" conformations and suggests specific for eEF1A1 affinity for Ca2+-calmodulin

BACKGROUND

Eukaryotic translation elongation factor eEF1A directs the correct aminoacyl-tRNA to ribosomal A-site. In addition, eEF1A is involved in carcinogenesis and apoptosis and can interact with large number of non-translational ligands. There are two isoforms of eEF1A, which are 98% similar. Despite the strong similarity, the isoforms differ in some properties. Importantly, the appearance of eEF1A2 in tissues in which the variant is not normally expressed can be coupled to cancer development.We reasoned that the background for the functional difference of eEF1A1 and eEF1A2 might lie in changes of dynamics of the isoforms.

RESULTS

It has been determined by multiple MD simulation that eEF1A1 shows increased reciprocal flexibility of structural domains I and II and less average distance between the domains, while increased non-correlated diffusive atom motions within protein domains characterize eEF1A2. The divergence in the dynamic properties of eEF1A1 and eEF1A2 is caused by interactions of amino acid residues that differ between the two variants with neighboring residues and water environment. The main correlated motion of both protein isoforms is the change in proximity of domains I and II which can lead to disappearance of the gap between the domains and transition of the protein into a "closed" conformation. Such a transition is reversible and the protein can adopt an "open" conformation again. This finding is in line with our earlier experimental observation that the transition between "open" and "closed" conformations of eEF1A could be essential for binding of tRNA and/or other biological ligands. The putative calmodulin-binding region Asn311-Gly327 is less flexible in eEF1A1 implying its increased affinity for calmodulin. The ability of eEF1A1 rather than eEF1A2 to interact with Ca2+/calmodulin is shown experimentally in an ELISA-based test.

CONCLUSION

We have found that reversible transitions between "open" and "close" conformations of eEF1A provide a molecular background for the earlier observation that the eEF1A molecule is able to change the shape upon interaction with tRNA. The ability of eEF1A1 rather than eEF1A2 to interact with calmodulin is predicted by MD analysis and showed experimentally. The differential ability of the eEF1A isoforms to interact with signaling molecules discovered in this study could be associated with cancer-related properties of eEF1A2.