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. 2003 Sep;85(3):1871-5.
doi: 10.1016/S0006-3495(03)74614-1.

Translational hydration water dynamics drives the protein glass transition

Alexander L Tournier  1 , Jiancong Xu, Jeremy C Smith
Affiliations

Translational hydration water dynamics drives the protein glass transition

Alexander L Tournier et al. Biophys J. 2003 Sep.

Abstract

Experimental and computer simulation studies have revealed the presence of a glass-like transition in the internal dynamics of hydrated proteins at approximately 200 K involving an increase of the amplitude of anharmonic dynamics. This increase in flexibility has been correlated with the onset of protein activity. Here, we determine the driving force behind the protein transition by performing molecular dynamics simulations of myoglobin surrounded by a shell of water. A dual heat bath method is used with which, in any given simulation, the protein and solvent are held at different temperatures, and sets of simulations are performed varying the temperature of the components. The results show that the protein transition is driven by a dynamical transition in the hydration water that induces increased fluctuations primarily in side chains in the external regions of the protein. The water transition involves activation of translational diffusion and occurs even in simulations where the protein atoms are held fixed.

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Figures

FIGURE 1
FIGURE 1
Mean-square fluctuations, 〈u2〉 of the protein nonhydrogen atoms for different sets of simulations. (a) ▪, control set with protein and solvent at same temperature; ♦, protein held at 80 K; •, solvent held at 80 K; ⋄, protein held at 180 K; ○, solvent held at 180 K. (b) Solvent held at 300 K. (c) Protein held at 300 K. Standard errors were estimated by calculating the mean-square fluctuations for 10 bins each 20 ps long.
FIGURE 2
FIGURE 2
Mean-square fluctuations of the protein side-chain heavy atoms for five different shells, each 4 Å thick (except for the inner shell (8 Å) and outer shell (6 Å)). The inset shows the difference in slopes of lines fitted below and above 220 K as a function of distance from the protein center of mass. Linear fits to the data above and below 220 K are also shown for the outermost shell.
FIGURE 3
FIGURE 3
Translational diffusion constant, formula image, for different sets of simulations. formula image, where formula image is the position of a water molecule oxygen atom at time interval formula image after an initial time formula image. For practical reasons formula image was set to 20 ps. formula image was calculated as the mean over 10 time intervals each 20 ps long. The errors were estimated using the standard deviation over the 10 intervals. (▪) Protein and solvent at same temperature; (▾) protein held fixed. Inset: the same data plotted as log Dtrans versus 1/T. Straight line fits below and above 220 K are also shown.
FIGURE 4
FIGURE 4
Excess mean-square fluctuation, formula image and excess water translational diffusion constant, DE versus temperature. formula image is defined as formula image where formula image is the linear part of 〈u2〉 obtained by fitting to the data below 220 K. formula image is calculated from formula image where formula image is the linear part of formula image obtained by fitting to the data below 220 K. All data calculated from the control simulations (protein and solvent at the same temperature).
FIGURE 5
FIGURE 5
Dipole rotational autocorrelation time on a logarithmic scale versus 1/T. The dipole rotational autocorrelation time was calculated by fitting to the correlation function formula image where formula image denotes the scalar product of the corresponding dipole vectors of unit length separated by a time t. The correlation times were calculated by fitting the correlation curves between 1.5 and 20 ps with a stretched exponential function. (▪) protein and solvent at same temperature (control); (▾) protein fixed.
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