Real Time Observation of Low-Temperature Protein Motions

Leeson, Daan Thorn; Wiersma, Douwe A.

doi:10.1103/physrevlett.74.2138

Cited by 61 publications

(31 citation statements)

References 21 publications

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“…(11 )). The existence of the hierarchy of substates has already been verified in several studies [1][2][3]. In analyzing an MD trajectory of crambin in solution [29,44] and in crystals we have seen similar phenomena and have shown that transitions from one basin of attraction to another do not conform to the traditional paradigm of diffusion or Markovian stochastic processes.…”

Section: Discussionmentioning

confidence: 67%

“…Proteins exhibit motions on a very wide range of timescales from picoseconds (ps) [1][2][3] to seconds [4] (as studied by hydrogen exchange experiments). Experimental studies on myoglobin suggest the existence of a hierarchy of motions occurring at various timescales and resulting from an ensemble of nearly degenerate states separated by a distribution of enthalpic energy barriers [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…In support of these observations Garcfa [29] showed that the fluctuations of a protein in solution are best described in terms of large-amplitude nonlinear motions. Molecular dynamics (MD) simulations, ligand recombination [30], pressure relaxation [7,8], time resolved X-ray crystallography [31 ] and vibrational echo studies [1][2][3] give information about the lower end of the funnel or energy landscape that is sampled in the folded state. Computational evidence (MD and Monte Carlo (MC) simulations) for the existence of these substates have been previously discussed in the literature [29,[32][33][34].…”

Section: Introductionmentioning

confidence: 99%

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Multi-basin dynamics of a protein in a crystal environment

Garcı́a

Blumenfeld

Hummer

et al. 1997

Physica D: Nonlinear Phenomena

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The dynamics of the small protein crambin is studied in the crystal environment by means of a 5.1 nanoseconds molecular dynamics (MD) simulation. The resulting trajectory is analyzed in terms of a small set of nonlinear dynamical modes that best describe the molecule's fluctuations. These modes are nonlinear in the sense that they describe a trajectory exhibiting multiple transitions among local minima at various timescales. Nonlinear modes are responsible for most of the protein atomic fluctuations. An ultrametric hierarchy of sampled local minima describes the protein trajectory when structures are classified in terms of their interconfigurational mean squared distance. Transitions among minima involve small changes in the relative atomic positions of many atoms in the protein. The character of the MD trajectory fits within the framework of rugged energy landscape dynamics. This MD simulation clarifies the unique statistical features of the barriers between minima in the energy-like configurational landscape. Longer timescale dynamics seem to sample transitions between minima separated by relatively higher barriers. The MD trajectory of the system in configurational space can be described in terms of diffusion of a particle in real space with a waiting time distribution due to partial trapping in shallow minima. A description of the dynamics in terms of an open Newtonian system (the protein) coupled to a stochastic system (the solvent and fast quasiharmonic modes of the protein) reveals that the system loses memory of its configurational space within a few picoseconds. The diffusion of the protein in configurational space is anomalous in the sense that the mean square displacement increases sublinearly with time, i.e., as a power law with an exponent that is smaller than unity.

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Section: Discussionmentioning

confidence: 67%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-basin dynamics of a protein in a crystal environment

Garcı́a

Blumenfeld

Hummer

et al. 1997

Physica D: Nonlinear Phenomena

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“…[1][2][3][4][5][6] This structural dynamics is associated with a spectral dynamics which can be conveniently measured by means of high resolution optical techniques, such as spectral hole burning, 1-5 stimulated photon echo, [6][7][8] or single molecule spectroscopy. [1][2][3][4][5][6] This structural dynamics is associated with a spectral dynamics which can be conveniently measured by means of high resolution optical techniques, such as spectral hole burning, 1-5 stimulated photon echo, [6][7][8] or single molecule spectroscopy.…”

Section: Introductionmentioning

confidence: 99%

Glasses and proteins: Similarities and differences in their spectral diffusion dynamics

Schlichter

Friedrich

2001

The Journal of Chemical Physics

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We compare the spectral diffusion dynamics of resorufin doped glycerol/H 2 O-and glycerol/ D 2 O-glass with the respective dynamics of a chromoprotein in the same glass at 4.2 K. Spectral diffusion broadening of photochemical holes is measured over almost four orders of magnitude in time. In all samples there are strong aging phenomena. Resorufin in deuterated water/glycerol is reasonably well-described by the two level system ͑TLS͒ model. In the protonated glass, the TLS model does not seem to describe the experiments reasonably well. In the protein sample it totally fails.

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“…The results showed that features in the energy landscape that were found at temperatures where the molecules become physiologically active (16) were also found in experiments below 1 K. These features are the roughness of the energy surface and the so-called deep minimum states. Quite recently, stimulated echo experiments on Zn-protophorphyrin-IXsubstituted myoglobin have shown that the self-similar organization of the energy landscape may even hold in a quantitative sense (17,18).…”

mentioning

confidence: 99%

Spectral diffusion and the energy landscape of a protein

Fritsch

Friedrich

Parak

et al. 1996

Proc. Natl. Acad. Sci. U.S.A.

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We present a novel type of spectral diffusion experiment in the millikelvin range to characterize the energy landscape of a protein as compared with that of a glass. We measure the time evolution of spectral holes for more than 300 hr after well-defined initial nonequilibrium conditions. We show that the model of noninteracting two-level systems can describe spectral diffusion in the glass, but fails for the protein. Our results further demonstrate that randomness in the energy landscape of a protein shows features of organization. There are ''deep minimum'' states separated by barriers, the heights of which we are able to estimate. The energy landscape of a glass is featureless by comparison.The folding routes, the three-dimensional structure, the dynamics, and the specific functions of a protein are all determined by the protein's energy landscape. This landscape is very complex and, hence, very difficult to measure (1), even qualitatively. What is well known, so far, is that despite the high level of structural organization (2), there is randomness in the energy landscape (3), which is reflected, for instance, in a variation of Debye-Waller factors in x-ray diffraction (4, 5), in inhomogeneous line broadening (6-8), in dispersive kinetics (9-11), and in spectral diffusion (6,8,(12)(13)(14). Much less is known about whether the randomness itself shows features of organization. It was suggested over a decade ago that the energy landscape of a protein may be organized in a hierarchical fashion (15). Recently, we found evidence for such self-similar features, although only in a qualitative sense, based on spectral diffusion experiments in the millikelvin range (13). The results showed that features in the energy landscape that were found at temperatures where the molecules become physiologically active (16) were also found in experiments below 1 K. These features are the roughness of the energy surface and the so-called deep minimum states. Quite recently, stimulated echo experiments on Zn-protophorphyrin-IXsubstituted myoglobin have shown that the self-similar organization of the energy landscape may even hold in a quantitative sense (17,18).

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Real Time Observation of Low-Temperature Protein Motions

Cited by 61 publications

References 21 publications

Multi-basin dynamics of a protein in a crystal environment

Multi-basin dynamics of a protein in a crystal environment

Glasses and proteins: Similarities and differences in their spectral diffusion dynamics

Spectral diffusion and the energy landscape of a protein

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