The dynamics of single protein molecules is non-equilibrium and self-similar over thirteen decades in time

Hu, Xiaohu; Hong, Liang; Smith, Micholas Dean; Neusius, Thomas; Cheng, Xiaolin; Smith, Jeremy C.

doi:10.1038/nphys3553

Cited by 158 publications

(172 citation statements)

References 26 publications

Supporting

Mentioning

159

Contrasting

Order By: Relevance

“…Further reports of subdiffusion come from the motion of proteins embedded in the membranes of living cells [24][25][26]. Subdiffusion is also seen in extensive simulations studies, for instance, of lipid bilayer membranes [27][28][29][30] and relative diffusion in proteins [31]. Superdiffusion, due to active motion of molecular motors, was observed in various biological cell types for both introduced and endogenous tracers [16,17,32,33].Most of the anomalous diffusion phenomena mentioned here belong to two main classes of anomalous diffusion: (i) the class of continuous time random walk processes, in which scale-free power-law waiting times in between motion events give rise to the law (3) [12,34], along with a stretched Gaussian displacement probability density G(x, t) [11,12,34] as well as weak ergodicity breaking and ageing [35,36].…”

mentioning

confidence: 88%

Random diffusivity from stochastic equations: comparison of two models for Brownian yet non-Gaussian diffusion

et al. 2018

View full text Add to dashboard Cite

A considerable number of systems have recently been reported in which Brownian yet non-Gaussian dynamics was observed. These are processes characterised by a linear growth in time of the mean squared displacement, yet the probability density function of the particle displacement is distinctly non-Gaussian, and often of exponential (Laplace) shape. This apparently ubiquitous behaviour observed in very different physical systems has been interpreted as resulting from diffusion in inhomogeneous environments and mathematically represented through a variable, stochastic diffusion coefficient. Indeed different models describing a fluctuating diffusivity have been studied. Here we present a new view of the stochastic basis describing time-dependent random diffusivities within a broad spectrum of distributions. Concretely, our study is based on the very generic class of the generalised Gamma distribution. Two models for the particle spreading in such random diffusivity settings are studied. The first belongs to the class of generalised grey Brownian motion while the second follows from the idea of diffusing diffusivities. The two processes exhibit significant characteristics which reproduce experimental results from different biological and physical systems. We promote these two physical models for the description of stochastic particle motion in complex environments. uncovered anomalous diffusion of the power-law formwith the anomalous diffusion exponent 0<α<1 and the generalised diffusion coefficient D α [11], for the motion of charge carriers in amorphous semiconductors [12]. With the advance of modern microscopy techniques, in particular, superresolution microscopy, as well as massive progress in supercomputing, anomalous diffusion of the type (3) has been reported in numerous complex and biological systems [13,14]. Thus, subdiffusion with 0<α<1 was observed for submicron tracers in the crowded cytoplasm of biological cells [15][16][17][18][19] as well as in artificially crowded environments [20][21][22][23]. Further reports of subdiffusion come from the motion of proteins embedded in the membranes of living cells [24][25][26]. Subdiffusion is also seen in extensive simulations studies, for instance, of lipid bilayer membranes [27][28][29][30] and relative diffusion in proteins [31]. Superdiffusion, due to active motion of molecular motors, was observed in various biological cell types for both introduced and endogenous tracers [16,17,32,33].Most of the anomalous diffusion phenomena mentioned here belong to two main classes of anomalous diffusion: (i) the class of continuous time random walk processes, in which scale-free power-law waiting times in between motion events give rise to the law (3) [12,34], along with a stretched Gaussian displacement probability density G(x, t) [11,12,34] as well as weak ergodicity breaking and ageing [35,36]. We note that similar effects of non-Gaussianity, weak non-ergodicity, and ageing also occur in spatially heterogeneous diffusion processes [37][38][39][40]. (ii) The secon...

show abstract

mentioning

confidence: 88%

Random diffusivity from stochastic equations: comparison of two models for Brownian yet non-Gaussian diffusion

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Dynamics is also very sensitive to environment, which leads to a well-structured system being inactive under certain solvent conditions18, and it is now fully accepted that further to structure being adapted to function, appropriate molecular motions are also necessary. Molecular dynamics on the picosecond to nanosecond time scale acts as the ‘lubricant’ of functional conformational changes on longer time scales192021. Following neutron scattering experiments, it has been proposed that adaptation occurs via evolutionary selection of dynamics on the thermal timescale22.…”

mentioning

confidence: 99%

The fluctuating ribosome: thermal molecular dynamics characterized by neutron scattering

Zaccaı̈

Natali

Peters

et al. 2016

Sci Rep

View full text Add to dashboard Cite

Conformational changes associated with ribosome function have been identified by X-ray crystallography and cryo-electron microscopy. These methods, however, inform poorly on timescales. Neutron scattering is well adapted for direct measurements of thermal molecular dynamics, the ‘lubricant’ for the conformational fluctuations required for biological activity. The method was applied to compare water dynamics and conformational fluctuations in the 30 S and 50 S ribosomal subunits from Haloarcula marismortui, under high salt, stable conditions. Similar free and hydration water diffusion parameters are found for both subunits. With respect to the 50 S subunit, the 30 S is characterized by a softer force constant and larger mean square displacements (MSD), which would facilitate conformational adjustments required for messenger and transfer RNA binding. It has been shown previously that systems from mesophiles and extremophiles are adapted to have similar MSD under their respective physiological conditions. This suggests that the results presented are not specific to halophiles in high salt but a general property of ribosome dynamics under corresponding, active conditions. The current study opens new perspectives for neutron scattering characterization of component functional molecular dynamics within the ribosome.

show abstract

“…Because available experimental data on the actual conformational transition networks in native proteins are still very poor, we constructed a model network to apply the theory for interpreting results of computer simulations. As mentioned in the Introduction, this network should be scale-free and display a transition from the fractal to small-world organization [15,16,17,18,19]. A sample network of 100 nodes with such property is depicted in Fig.…”

Section: Specification Of the Computer Modelmentioning

confidence: 99%

“…The rule are fluctuating rates of the catalyzed reactions (the "dynamic disorder") [8,9,14], which means realization of them in various randomly selected ways. As a symbol of the progress made recently, the molecular dynamics study of conformational transitions in the native phosphoglycerate kinase could be quoted, in which a network of 530 nodes was found in the long 17 µs simulation [15]. This network seems to display a transition from the fractal to small-world organization [16,17].…”

Section: Introductionmentioning

confidence: 99%

Information processing in biological molecular machines

Kurzynski

Chelminiak

2020

Preprint

View full text Add to dashboard Cite

Biological molecular machines are enzymes that simultaneously catalyze two processes, one donating free energy and second accepting it. Recent studies show that most native protein enzymes have a rich stochastic dynamics of conformational transitions which often manifests in fluctuating rates of the catalyzed processes and the presence of short-term memory resulting from the preference of certain conformations. For arbitrarily complex stochastic dynamics of protein machines, we proved the generalized fluctuation theorem predicting the possibility of reducing free energy dissipation at the expense of creating some information stored in memory. That this may be the case has been shown by interpreting results of computer simulations for a complex model network of stochastic transitions. The subject of the analysis was the time course of the catalyzed processes expressed by sequences of jumps at random moments of time. Since similar signals can be registered in the observation of real systems, all theses of the paper are open to experimental verification. STATEMENT OF SIGNIFICANCEThe transient utilization of memory for storing information turns out to be crucial for the movement of protein motors and the reason for most protein machines to operate as dimers or higher organized assemblies. From a broader physical point of view, the division of free energy into the operation and organization energies is worth emphasizing. Information can be assigned a physical meaning of a change in the value of both these functions of state.

show abstract

The dynamics of single protein molecules is non-equilibrium and self-similar over thirteen decades in time

Cited by 158 publications

References 26 publications

Random diffusivity from stochastic equations: comparison of two models for Brownian yet non-Gaussian diffusion

Random diffusivity from stochastic equations: comparison of two models for Brownian yet non-Gaussian diffusion

The fluctuating ribosome: thermal molecular dynamics characterized by neutron scattering

Information processing in biological molecular machines

Contact Info

Product

Resources

About