Computational methods for predicting sites of functionally important dynamics.
Authors Schuyler AD, Carlson HA, Feldman EL
Submitted By Eva Feldman on 3/24/2010
Status Published
Journal The journal of physical chemistry. B
Year 2009
Date Published 5/14/2009
Volume : Pages 113(19) : 6613 - 6622
PubMed Reference 19378962
Abstract Understanding and controlling biological function of proteins at the atomic
level is of great importance; allosteric mechanisms provide such an interface.
Experimental and computational methods have been developed to search for residue
mutations that produce changes in function by altering sites of correlated
motion. These methods are often observational in that altered motions are
achieved by random sampling without revealing the underlying mechanism(s). We
present two deterministic methods founded on structure-function relationships
that predict dynamic control sites (i.e., locations that experience correlated
motions as a result of altered dynamics). The first method ("static") is based
on a single structure conformation (e.g., the wild type (WT)) and utilizes a
graph description of atomic connectivity. The local atomic interactions are used
to compute the propagation of contact paths. This description of structure
connectivity reveals flexible locations that are susceptible to altered
dynamics. The second method ("dynamic") is a comparative analysis between the
normal modes of a WT structure and a mutant structure. A mapping function is
defined that quantifies the significance of the motions in one structure
projected onto the motions of the other. Each mode is considered up- or
down-regulated according to its change in relative significance. This
description of altered dynamics is the basis for a motion correlation analysis,
from which the dynamic control sites are readily identified. The methods are
theoretically derived and applied using the canonical system dihydrofolate
reductase (DHFR). Both methods demonstrate a very high predictive value
(p<0.005) in identifying known dynamic control sites. The dynamic method also
produces a new hypothesis regarding the mechanism by which the DHFR mutant
achieves hyperactivity. These tools are suitable for allosteric investigations
and may greatly enhance the speed and effectiveness of other computational and
experimental methods.

Investigators with authorship
Eva FeldmanUniversity of Michigan


Dhfrdihydrofolate reductase