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review
Dynamic activation of protein function:
A view emerging from NMR spectroscopy
© 2001 Nature Publishing Group http://structbio.nature.com
A. Joshua Wand1
Recent developments in solution NMR methods have allowed for an unprecedented view of protein dynamics.
Current insights into the nature of protein dynamics and their potential influence on protein structure, stability
and function are reviewed. Particular emphasis is placed on the potential of fast side chain motion to report on
the residual conformational entropy of proteins and how this entropy can enter into both the thermodynamic
and kinetic aspects of protein function.
The physical basis of protein structure, dynamics and function
has been intensely studied for several decades. In the midst of the
rush to pursue structural genomics, a quieter revolution in the
use of solution NMR relaxation methods to characterize internal
protein motion has also begun. Although the influence of structure in molecular recognition and catalysis by proteins is well
appreciated, the role of dynamics is largely unknown and often
ignored. Nevertheless, it has long been recognized that proteins
are indeed dynamic systems. Early insights into the timescale
and character of protein internal motion largely employed local
optical probes, unresolved hydrogen exchange, and one-dimensional NMR techniques that, while limited, revealed a startling
complexity and richness in the internal motion of proteins1–4.
These initial views contributed significantly to the development
of current treatments of protein dynamics and thermodynamics5,6. The connection to biological function rather than just biological form is more recent. Internal protein dynamics can
potentially affect protein function through a variety of mechanisms, some of which are tautological or obvious in nature while
others are subtle and remain to be fully explored and appreciated. There are now several examples of protein–protein and protein–ligand interactions that illustrate that dynamics may be
fundamentally linked to function in several ways. This review
provides a brief summary of recent developments in solution
NMR methods that allow for an unprecedented view of protein
dynamics. How dynamics can enter into fundamental thermodynamic and kinetic aspects of protein function is also reviewed
and illustrated with intriguing results from several systems that
point to a promising future for this area of inquiry.
resolved21. These advances have positioned solution NMR spectroscopy to efficiently and comprehensively characterize the fast
internal dynamics of proteins of significant size.
NMR relaxation experiments can be used to probe the subnanosecond motion of interaction (bond) vectors within the
molecular frame. Observable NMR relaxation parameters, such
as the spin-lattice (T1) and spin-spin (T2) relaxation times of a
nuclear spin are directly related to the spectral density, J(ω),
describing the motion of the involved interaction vector. The
spectral density is in turn directly related, by real Fourier transform, to the time domain correlation function defining this
motion in the laboratory frame. Thus, in liquids, the motion of
an interaction vector includes both global macromolecular tumbling and motion within the macromolecular frame. The former
is uninteresting here but important for obtaining information
about the latter. This situation is most commonly analyzed by
separate treatment of the contributions of overall molecular
reorientation and internal motion. The correlation function for
internal motion then becomes:
CI(t) = <P2(û(0)û(t))>
(1)
where P2 is the second Legendre polynomial and û is the unit
vector that describes the orientation of the interaction (bond)
vector in the macromolecular frame. The functional form of the
internal correlation function, and its counterpart spectral density, is usually obtained from the so-called 'model free' treatment
developed by Lipari and Szabo22. This approach considers, with
much justification, the internal correlation function as a simple
exponential. This functional form in turn results in a Lorentzian
Using solution NMR to characterize protein dynamics
spectral density. The limiting value of the internal correlation
The emerging success of NMR spectroscopy in the arena of pro- function gives a model-insensitive measure of the degree of spatein dynamics rests on four general areas of development over tial restriction of the underlying motions. This limiting value is
the past decade. First and perhaps foremost, triple resonance used to define the squared generalized order parameter22:
NMR spectroscopy now provides an efficient and robust set of
(2)
S2 = (4π/5) ∑|<Y2,m(Ω)>|2
tools for the comprehensive resonance assignment of proteins of
significant size7. These methods, in turn, derive much of their
power from companion isotopic enrichment strategies8,9, which where Y2,m corresponds to the second order spherical harmonic
have been subsequently refined to allow for isotopic labeling pat- functions and Ω corresponds to the polar angles of û. The generterns that are optimized for NMR relaxation studies10–16. Two- alized order parameter is then a measure of the amplitude of
dimensional sampling of relaxation has allowed for motion of the interaction vector within the molecular frame
comprehensive studies to be efficiently undertaken12,17–20, albeit (Fig. 1), with limiting values of unity, corresponding to comwith great instrumental cost. A variety of technical issues such as plete rigidity, and zero, corresponding to isotropic motion. The
the effects of macromolecular tumbling and the influence of effective correlation time, τe, provides an upper limit on the
competing relaxation mechanisms have also been largely timescale of the underlying motions and is formally defined as
The Johnson Research Foundation & Department of Biochemistry & Biophysics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA. email:
[email protected]
1
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sym
. ax
is
Fig. 1 Illustration of various motions affecting the obtained generalized
order parameters for methyl deuterons. Shown is the isopropyl fragment
of a leucine side chain. The trivial motion about the symmetry axis of the
methyl group occurs on a picosecond timescale. Because the geometry of
the methyl group is known, the effects of methyl rotation on relaxation
can be directly accounted for and the motion of the methyl symmetry
axis (the Cβ–Cγ bond) revealed. Local torsional oscillations about the
Cβ–Cγ bond can be accompanied by additional remote torsional oscillations and bond vibrations, which would result in mutations about the
path defined by the indicated simple rotation and a distribution of
motions within the elliptical cone shown. The square of the generalized
order parameter for the symmetry axis of the leucine δ-methyl groups
(S2axis) reports on these kinds of motions occurring on timescales up to
the timescale of global molecular reorientation, which is on the order of
5–20 ns for proteins currently accessible by NMR relaxation methods.
Similar motions are anticipated for other methyl-bearing amino acid
residues. Reproduced with permission from Lee et al.42.
© 2001 Nature Publishing Group http://structbio.nature.com
sym
. axis
χ2
the area under the internal correlation function22. The key to
what will follow below is that the generalized order parameter
therefore provides access to the equilibrium probability distribution of the interaction vector:
S2 = ∫∫dΩ1δΩ2peq(Ω1)P2(cosθ12)peq(Ω2)
(3)
where the integrals are over all possible pairs of orientations of
the interaction vector û, scaled as a function of the angle (θ)
between them and weighted by the probabilities of each orientation. In principle, an experimental generalized order parameter
can be parametrically related to thermodynamic parameters
through the angular partition functions, peq, derived from a
model potential energy function.
The nature of protein dynamics
Dozens of 15N relaxation-based studies of backbone dynamics
have been reported and generally indicate that the main chain
largely acts as a rigid scaffold23,24. This is not to say that the main
chain does not participate in functionally relevant dynamics
since there are clear instances where main chain dynamics report
on the thermodynamics of protein function (for example, see
ref. 25). However, the dynamic behavior of the side chains is
apparently more complex and varied than the main chain. Initial
views of side chain dynamics provided by 13C and 2H NMR relaxation methods suggested that protein hydrophobic cores are
quite dynamic and, importantly, heterogeneously so10–13,26,27. The
handful of studies of the fast subnanosecond motion of methylbearing side chains reveal a remarkably rich range of motion. A
recent surprise is the apparent clustering of methyl-bearing side
chains into three general classes of dynamic disorder28. First recognized in a study of a calmodulin–peptide complex, this behavior was retrospectively identified in data obtained on other
proteins28 (Fig. 2). The physical origin of the multimodal distribution of angular side chain order is unclear but it does raise the
possibility that classifications analogous to protein secondary
structural motifs may exist for dynamic modes of proteins. If
true, this opens up an entirely new vista for the biological role of
fast internal protein dynamics in biology — that is, dynamics
may be an evolutionarily determined parameter of proteins.
Interestingly, initial studies of proteins bearing tightly bound
heme29 or flavin30 prosthetic groups suggest that large amplitude
motions may be generally suppressed in proteins binding large
inflexible prosthetic groups (Fig. 2). In contrast, a well-structured and thermally stable protein of de novo design was found
to have a distribution including the two ‘bands’ corresponding
to high and intermediate amplitudes of motion but missing the
nature structural biology • volume 8 number 11 • november 2001
class of amino acids with highly restricted motion31 (Fig. 2).
Thus, even with these few examples, it seems clear that yet to be
discovered features of native-like protein structure may lead to a
surprising range of dynamic character in the subnanosecond
time regime.
The structural and stereochemical determinants of this rich
dynamic behavior are largely unknown. It is reasonable that certain structural features may modulate the extent of motions possible for particular side chain elements. For example, it seems
physically plausible that the fewer the number of degrees of freedom by which a given methyl group is separated from the relatively rigid polypeptide backbone, the more correlated its
motion should be with the motion of its associated amide N–H.
For proteins studied thus far, this is clearly true for alanine,
isoleucine-γ2 and threonine methyl groups, less accurate for
valine and not true for leucine, isoleucine-δ and methionine
methyl groups. There is also no correlation with the degree of
accessible surface area32 and only one case with even a hint of a
correlation with depth of burial30. Indeed, some of the most
dynamically disordered methyls are the δ methyls of Ile residues
in the hydrophobic cores of proteins. One might also anticipate
that regions of fluidity and rigidity should exist in proteins.
Clustering of ordered and disordered side chains has not been
noted in the smaller proteins studied but is apparent in HIV protease33 and flavodoxin30. These are two of the larger proteins
studied thus far, which may be hinting at the need to study the
internal dynamics of even larger proteins in order to confirm
and more fully characterize this dependency and its physical origins. Importantly, from the few cases where both main chain
and side chain dynamics have been investigated in the same protein, it is also now clear that there can be a complete decoupling
of the dynamics of side chains from the dynamics of the main
chain. Thus the behavior of the main chain is not a reliable predictor of the dynamics of the attached side chains34.
Protein dynamics and entropy
Although the empirical view of the internal dynamics of proteins is itself interesting, it is what these insights can tell us about
protein function that is most intriguing. The dynamics of proteins enter into considerations of protein function at many levels. From a thermodynamic point of view, the fast internal
dynamics of proteins have the potential to report on the number
of states that a given site in a protein explores (Eq. 3) and hence,
in principle, can act as an ‘entropy meter’. From a kinetic perspective, internal motions may have evolved to actively promote
catalytic activity in enzymes. Let us first discuss the thermodynamic perspective.
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Fig. 2 Distributions of the amplitude of fast dynamics of methyl-bearing
side chains in proteins. Shown are histograms of the distribution of
squared generalized order parameters of methyl group symmetry axes
(S2axis) obtained from deuterium relaxation experiments of a, ubiquitin27,
b, cytochrome c2 (ref. 29) and c, a protein of de novo design, α3D
(ref. 31). The distribution seen for ubiquitin is trimodal and may be representative of native state proteins without bound ligands (see also
Fig. 3). In contrast, the distribution seen for cytochrome c2 largely lacks
the high amplitude (low S2) population, has a greatly diminished population of methyl-bearing side chains undergoing intermediate amplitude
motion and a greatly enhanced population of effectively rigid methylbearing side chains. The behavior of α3D, a well-structured and stable
protein of de novo design, indicates that few methyl-bearing side chains
are rigid and a relatively large fraction are undergoing extensive motion
on the subnanosecond timescale. These few examples illustrate the
great range of dynamic behavior that well-packed and stable proteins
can display.
In so far as dynamic modes of proteins represent transitions
between conformational states, internal motion is an indirect
measure of the residual entropy of the folded state. NMR spectroscopy gains access to the entropy through the angular distribution functions of Eq. 3, which are directly related to the
partition function of the system. The partition function (Q)
defines thermodynamic parameters of the system through the
usual expressions for the Helmholtz free energy (A), enthalpy
(H) and entropy (S):
a
b
c
A = -kT ln Q
H = kT2 (∂ ln Q / ∂ T)
S = k ln Z + kT (∂ ln Q / ∂ T)
The parametric connection between the experimental S2 and a
measure of a thermodynamic quantity such as the free energy or
entropy requires specification of a physical model25. Two primitive potential energy functions are commonly employed for this
purpose: ‘free diffusion within a cone’, which corresponds to diffusion in a square well potential, and harmonic oscillator treatments, corresponding to diffusion within a quadratic
potential35–37. Both models have been used with some utility to
convert experimental measures of local dynamics into estimates
of local residual entropy and derived quantities such as heat
capacity. However, the models themselves are clearly limited in
their capacity to adequately interpret experimental measures of
protein dynamics. For example, the ‘diffusion within a cone’
model has no intrinsic heat capacity since it is defined by a
square-well potential and would predict temperature-independent dynamics. Yet initial temperature studies of fast main chain
and side chain dynamics generally reveal significant changes in
S2 with temperature28,38. The harmonic oscillator model predicts
a roughly linear temperature dependence of S2 in the temperature regime accessible to solution NMR methods35. Qualitatively,
this dependence is observed for many side chain sites in a
calmodulin–peptide complex, but numerous exceptions
abound38 (Fig. 3). Clearly, the densely packed interior of the protein introduces physical features that are not accommodated at
all by the simple physical models. Significant work in this area is
required, particularly in the development of physical models
that provide insight into the rich and varied dynamics of amino
acid side chains that are observed.
From the initial stages, it has been recognized that the simple
site-resolved inventory of entropy ignores the very real possibility of correlated motion and the fact that single probes in a side
chain need not sense all motions that are present. The latter difficulty is simply dealt with by employing several probes throughout the side chain, with the attendant increase in experimental
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burden. For example, experimental strategies for characterizing
motion at methylene sites in large proteins exist39 and in principle will allow the potentially complex motions of long aliphatic
side chains to be more completely characterized. The issue of
correlated motion is somewhat resistant to direct resolution37.
Here perturbation techniques such as mutagenesis, temperature
or pressure studies may be most useful in delineating the presence and nature of coupling of side chain motions in densely
packed protein interiors. Temperature provides direct access to
the energetics of the underlying motions. Pressure offers the
potential to differentiate ‘diffusive’ from ‘jump-like’ motions —
that is, to distinguish motion of a group that continuously
sweeps out a volume from one where the group rapidly jumps
between a small number of discrete, equally well-packed states.
Wagner40 has used this approach to successfully characterize the
nature of aromatic ring motion in proteins. Again, these
approaches will require an enormous experimental effort to
carry through but appear to be necessary for a firm understanding of the nature of internal motion in proteins.
Consequences of protein entropy
Notwithstanding the limitations of the interpretative models
that are currently employed, it is now clear that proteins have
considerable residual entropy and that changes in functional
state are often associated with changes in the magnitude and,
most importantly, the distribution of this residual entropy. This
will impact our view of protein structure, stability and dynamics
in several respects. For example, in the classical view of the thermodynamics of protein folding and stability, it is argued that the
penalty of going from an unfolded state of high entropy to a
folded state of low residual entropy is largely overcome by the
entropic gain derived from the release of water solvating
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Fig. 3 Fast dynamics of methyl-bearing side chains in a calmodulin-peptide complex. The temperature dependence of S2axis values of methylbearing amino acids of calmodulin in complex with a peptide
corresponding to the calmodulin-binding domain of the smooth muscle
myosin light chain kinase. Members of the three classes of motion are
color coded. Whereas many of the methyl sites display the linear temperature dependence predicted for a harmonic oscillator35, many are relatively temperature insensitive and others are temperature dependent in
a highly nonlinear fashion. Data of this kind may hold the promise of
detecting and documenting correlated motion in proteins as well as providing site-resolved information about the energetics of internal protein
motion. Reproduced with permission from Lee & Wand28.
1.0
0.8
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2
0.6
Saxis
0.4
0.2
0.0
290
300
310
320
330
340
Temperature (K)
hydrophobic groups in the unfolded state. The conformational
entropy of the unfolded state has recently be re-assessed and
argued to be much smaller than previously imagined41. The view
provided by NMR spectroscopy that the residual entropy of the
folded state may be large further diminishes the entropic penalty
that a protein must pay to fold, in effect narrowing the top and
broadening the bottom of the energy landscape funnel.
The potential for a change in conformational entropy in
response to a change in functional state also has important ramifications. For example, we have used deuterium NMR relaxation methods to investigate the changes in conformational
entropy of calmodulin upon complexation with a peptide comprising the calmodulin-binding domain of the smooth muscle
myosin light chain kinase42. Upon binding to this target domain,
calmodulin undergoes a widespread redistribution in side chain
dynamics, which is interpreted to correspond to an estimated
overall change in conformational entropy of approximately
–35 kcal mol–1 at 308 K. This is an impressive change in entropy.
The dynamic character of the main chain is largely unaffected by
the binding of the target domain, emphasizing that the dynamic
behavior of the main chain need not be correlated with the
response of the side chains.
In the small number of cases examined thus far, the response
of proteins to binding of both large and small ligands is remarkably varied. A particularly interesting example is the recent study
of three different functional states of Cdc42Hs, a member of the
Ras superfamily of GTP-binding proteins43. Members of this
family are activated by the exchange of GDP for GTP. Cdc42Hs
interacts with a variety of proteins that serve to control signal
transduction. Loh et al.43 characterized the dynamics of backbone amide NH and side chain methyls of Cdc42Hs in complex
with GDP, GTP and a domain derived from the p21-activated
kinase effector of Cdc42Hs. 15N-relaxation studies indicated that
activation (replacement of GDP with a nonhydrolyzable analog
Fig. 4 Dynamics, entropy and allostery. A simple schematic illustration of
allosteric mechanisms a, based solely on a change in atomic coordinates
of the protein and b, based solely on entropic effects manifested in the
dynamics of the protein. Structure-based allostery is the current paradigm but as pointed out by Cooper & Dryden44, a change in conformational entropy also provides a plausible mechanism for creation of
allosteric free energy changes in proteins. Only small changes in the
breadth of the conformational distribution would be required if a large
number of motional modes are involved. c, In principle, both mechanisms could be operative.
nature structural biology • volume 8 number 11 • november 2001
of GTP) has little effect on the dynamics of the backbone, while
binding of the effector domain results in a significant decrease in
the complexity of the backbone motion with the dynamics being
shifted and confined to shorter timescales43. Similarly, the activation of Cdc42Hs results in only small perturbations of the
motion of methyl-bearing side chains in the protein43. The binding of the effector domain, however, has a very intriguing effect
— it causes a general increase in side chain mobility that is most
pronounced for residues remote from the effector–Cdc42Hs
interface.
These observations point not only to a considerable and heterogeneously distributed residual protein entropy but also to
large changes in that entropy upon a change in functional state.
This result raises the exciting possibility that proteins have
adopted entropic effects to carry out allosteric phenomena.
Some time ago, Cooper and Dryden44 described a plausible
model for allostery that arises from such changes in the distribution of fluctuations about the mean structure of the protein. The
potential for statistical thermodynamic linkage between conformational and binding equilibria is being actively explored by a
number of groups45,46. An entropically-based allosteric mechanism could, in principle, be combined with the more classical
mechanical or ‘enthalpic’ view where discrete conformational
change defines the allosteric transition (Fig. 4). The central
point is that if a large number of dynamic modes of the protein
are involved in this sort of allosteric mechanism then the change
in conformational ‘breadth’ (the width of the distributions
shown in Fig. 4) need be on the order of only a fraction of an
angstrom to provide free energy changes (∆∆G) typical of
allosteric activation. It is therefore not surprising that this sort of
mechanism, if it exists, has not yet been revealed by structural
methods such as X-ray crystallography. NMR spectroscopy
appears to provide the best hope for confirming or disproving
the adoption of such allosteric mechanisms in proteins.
a
b
c
Structural Coordinates
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Dynamic origins of enzyme catalysis
Structural studies have largely supported the view of Pauling
that the immense catalytic power of enzymes originates in their
greater affinity for the transition state than for the ground state
substrate47. This preference can occur through stabilization of
the transition state47 and/or destabilization of the ground state48.
A supplementary view is that enzymes position reactants to
allow thermal motions to carry them efficiently along the reaction coordinate49,50. It remains a major experimental challenge,
however, to reveal the role of protein dynamics in the interconversion of catalytic complexes and for directly promoting chemical catalysis on the surface of the protein. For example, such a
role for protein fluctuations in promoting hydrogen tunneling
during catalysis by alcohol dehydrogenase has been proposed51
and recently reinforced52. The potential influence of protein
dynamics on electron transfer has also recently been illuminated53. In that case it was argued that dynamic fluctuations have
the potential to relieve destructive interference inherent in a
multipathway view of protein mediated electron transfer.
Interestingly, the reduced state of the electron transfer protein
cytochrome c2 has been found to have an unusually rigid interior29. It remains to be determined, however, whether this is a
simple consequence of the presence of a large rigid heme moiety
in the core of the protein or whether rigidity is directly relevant
to the electron transfer properties of the system.
Fundamental questions about the role of protein dynamics in
the kinetics of enzyme catalysis clearly remain. Are the general
thermally activated random motions of the protein harnessed
for catalysis or are ‘special’ fluctuations employed? What is the
timescale of kinetically relevant motion? It need not be on the
timescale of the catalytic rate constant. Here the breadth of
timescales accessible by NMR methods is an important advantage, because the functionally relevant motion can in principle
occur on timescales as slow as that defined by the corresponding
catalytic rate constant. If the catalytic event is strongly coupled
to a given motion then they will be highly correlated and occur
on the same timescale. If they are not strongly coupled then it
may take many dynamic events before catalysis is realized. In
that case, the functionally relevant motion may occur on a much
faster timescale than that defined by the timescale of the functional event34. The latter scenario demands that the NMR spectroscopist investigate dynamic phenomena from the millisecond
to the picosecond time regimes. Specialized approaches are
required to access processes occurring in the microsecond to
millisecond time regime.
As outlined above, classical relaxation experiments provide
access to the picosecond to nanosecond time regime. Deviations
of observed T2 relaxation times from values predicted by other
relaxation parameters, such as T1 and the NOE, or deviation
from the predicted magnetic field dependence have often been
used as evidence for motion in the millisecond time regime.
These approaches are relatively insensitive and fraught with
technical issues. Fortunately, recent advances in the implementation of relaxation dispersion experiments now allow for efficient and, importantly, sensitive investigation of the
millisecond-microsecond time regimes19,20. These experiments
rely on a change in the resonance frequency of a given nucleus as
it moves from one state to another. This change is an indirect
930
reporter of dynamics; a significant potential limitation is the
possibility that a remote change in structure induces a change in
the reporter resonance frequency. Careful consideration is
required to accommodate this possibility in the analysis of dispersion relaxation data and ascribe the apparent dynamic mode
to a particular structural element.
There are only a few examples of the definitive correlation of
function with structural fluctuations occurring on the millisecond timescale. In addition to the apparent importance of
changes in residual protein entropy represented by changes in
fast dynamics described above, the calmodulin system also provides an example of the correlation of changes in motion in the
microsecond to millisecond time regime with a change in functional state. The cooperative binding of calcium to calmodulin
results in the transition of the apo state, which is characterized
by extensive backbone µs–ms timescale motion, to the holo
state, where these motions are largely dampened54. Changes in
motion in this time regime are also potentially important in protein–protein recognition. For example, as part of an investigation of the mechanism of action of the Bacillus subtilis response
regulator Spo0F, Feher and Cavanagh55 detected millisecond
timescale motion that correlated with residues and surfaces
known to be critical for protein–protein interactions. Similarly,
Volkman et al.56 found a strong correlation between phosphorylation-driven activation of the signaling protein NtrC and
microsecond timescale motion of the backbone in regions
undergoing structural transition upon activation. In these situations the dynamics are often considered to be restricted to interconversion of two states and involve relatively large elements of
structure. One is therefore tempted to suggest that the change in
entropy reflected by these dynamic modes is small and that the
dynamic measurements are reporting on the transition between
inactive and active forms of the protein.
Summary
As a result of a variety of recent advances, solution NMR spectroscopy is well positioned to contribute significantly to our
growing understanding of the role of protein dynamics in function. Intriguing glimpses of the richness of protein dynamics
propel continuing studies. Important thermodynamic insights
are accessible by virtue of the counting of states implicit in
dynamics and may allow direct characterization of an experimentally elusive component of free energy in protein systems,
the residual conformational entropy. Many NMR-based methods exist to probe protein dynamics over a wide range of
timescales. Here we have concentrated on NMR relaxation techniques but other approaches, such as partial averaging of dipolar
couplings57, also hold significant promise for characterizing
transitions within and between various functional states of proteins. Thus the future is bright and one anticipates a fast-paced
exploration of protein structural dynamics by the NMR community will soon begin.
Acknowledgments
I thank A. Palmer, K. Sharp and W. Englander for helpful discussion. This work
was supported by grants from the NIH.
Received 3 August, 2001; accepted 17 September, 2001
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