I present evidence that cooperative motions of functional dynamics can be
extracted from ordinary, average electron density data using nothing more
than established geometry restraint information. A robust scoring function
is in hand, but an efficient approach to untangling the chains of multi-
conformer models is needed. This underappreciated tangling phenomenon
arises from the density term, not chemical geometry restraints, but
nevertheless these tangles prevent current refinement programs from
finding a way to simultaneously satisfy both kinds of data: observed density
and prior knowledge of intramolecular forces. To demonstrate, I have
prepared examples of a simple 2-state system with increasing degrees of
tangling complexity. Moreover, the model with the best score reflects the
true, underlying cooperative motion of the system, and the more untangled
the model gets it both becomes closer it is to this true ensemble and it also
becomes easier to detect the tangles. This finding implies that not only will
untangling multi-conformer models lead to better geometry scores and
lower R factors, but also reveal more biologically relevant cooperative
motions. A global challenge data set with cash prizes will be announced.