Highly constrained simulations

A third area where continuum solvent models are useful is in highly constrained simulations. These include X-ray crystallographic and 2D-NMR structural refinements. In these situations, with the additional restraints (and additional computation) arising from the experimental data, the extra expense of explicit solvent models would be inappropriate. 

To facilitate conformational transitions in the before-mentioned adenylate kinase, Elamrani and co-workers scaled all atomic masses by a large factor thus allowing the use of a high effective simulation temperature of 2000K ([Elamrani et al. 1996]). To prevent protein unfolding, elements of secondary structure had to be constrained. 

One reason for the inefficiencies of constraint methods is that they may prevent an efficient sampling of the set (x) = . This is illustrated by Fig. 4.2. It is common that many pathways separated by high energy barriers exist to go from A to B. In constrained simulation, the system can get trapped in one of the pathways. In the most serious cases, this leads to quasi-nonergodic effect where only a part of the set (x) is effectively explored. In less serious cases, the convergence is quite slow. 

The recent development of internal coordinate quantum Monte Carlo has made it possible to directly compare classical and quantum calculations for many body systems. Classical molecular dynamics simulations of many body systems may sometimes overestimate vibrational motion due to the leakage of zero point energy. The problem appears to become less severe for more highly connected bond networks and more highly constrained systems. This suggests that current designs of some nanomachine components may be more workable than MD simulations suggest. Further study of classical-quantum correspondence in many body systems is necessary to resolve these concerns. 

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