The NEIMO method has now been successfully applied to polypeptide and protein systems. The method is extremely fast compared to other internal-coordinate dynamics methods, as it scales linearly with the number of degrees of freedom. For increasingly large systems, the NEIMO computational requirements grow more slowly than those for energy calculations, thereby allowing for its applicability to extremely large systems. Molecular dynamics of only torsional degrees of freedom can use larger timesteps than simulations allowing all possible degrees of freedom. NEIMO calculations of peptides indicate that timesteps as large as 20 femtoseconds can be used for these small systems. Timesteps of this size are not yet possible for large polypeptides and proteins, as judged by the criterion of total energy fluctuations. However, timesteps of 5 fs and longer can be used for large systems without danger of energy divergence; such calculations may be useful for conformational analyses of extremely large systems such as viruses. The use of a different integration method may improve the energy conservation for larger systems.
The dynamics of polypeptides are accurately modeled by the NEIMO method. Analyses of dihedral angle fluctuations show that NEIMO dynamics simulations produce conformational fluctuations very similar to those arising from Cartesian dynamics simulations. The few exceptions to this in simulations of Met-enkephalin appear to be cases where rotational barriers are traversed in the Cartesian dynamics simulation, but not in a NEIMO simulation at the same temperature. It is likely that fixing bond angles keeps rotational barriers higher than in a more flexible model. Future implementations of the NEIMO method for molecular systems will include the additional hinge degrees of freedom, allowing for flexibility in these angles.
We would like to acknowledge the indispensable help of Dr. Abhinandan Jain of the Jet Propulsion Laboratory in providing the spatial operator codes for the core computations in our molecular version of NEIMO dynamics. We also wish to thank Dr. Guillermo Rodriguez of JPL and Dr. N. Vaidehi of Caltech for their important contributions to the development of the methodology and the current implementation. AMM acknowledges a National Research Service Award/NIH Predoctoral Traineeship in Biotechnology.