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Although we only explored the application of our method to the prediction of ligand-
induced conformational change, many other potential applications exist. For example,
one could use it to economically study the conformational dynamics of a protein. Pang et
al performed one such study, modeling the domain movements of Glutamine binding
protein. They reported taking 42 computer days to simulate 6ns, approximately
3,000,000 time steps, of this protein’s motion, comparable to the 5ns known to be
required for ligand binding. The analysis was performed for the apo structure as well as
for a “closed-apo” structure generated by removing the ligand from a holo protein-ligand
complex. Despite the expense, the open conformer was not observed to close (probably
in part because no ligand was present) and the “closed-apo” structure was not observed to
open. A trajectory connecting open and closed states from an ensemble generated by the
Conformation Explorer could potentially be used with umbrella sampling to compute the
relative stabilities of open vs. closed conformer, as well as the height of any barrier
separating them.
As another potential application, one could find a physically reasonable trajectory of
motion connecting two conformations of a protein, simply by following the sRMSD
gradient from the starting structure as M domain orientation approaches that of a given
target structure. This would be similar to interpolated (“morphed”) trajectories
generated by the Database of Macromolecular Motions (MolMovDB.org). That server
provides two main methods of obtaining morph trajectories[30]: the adiabatic morphing
of Krebs et al.[109] and FRODA[60]. Adiabatic morphing consists of a iterative linear
interpolations of atomic coordinates between two submitted structures, followed by
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