Conformational Motions Of Proteins Research Articles

Changes in hydration structure are necessary for collective motions of a multi-domain protein.

Conformational motions of proteins are necessary for their functions. To date, experimental studies measuring conformational fluctuations of a whole protein structure have revealed that water molecules hydrating proteins are necessary to induce protein functional motions. However, the underlying microscopic mechanism behind such regulation remains unsolved. To clarify the mechanism, multi-domain proteins are good targets because it is obvious that water molecules between domains play an important role in domain motions. Here, we show how changes in hydration structure microscopically correlate with large-amplitude motions of a multi-domain protein, through molecular dynamics simulation supported by structural analyses and biochemical experiments. We first identified collective domain motions of the protein, which open/close an active-site cleft between domains. The analyses on changes in hydration structure revealed that changes in local hydration in the depth of the cleft are necessary for the domain motion and vice versa. In particular, ‘wetting’/‘drying’ at a hydrophobic pocket and ‘adsorption’/‘dissociation’ of a few water molecules at a hydrophilic crevice in the cleft were induced by dynamic rearrangements of hydrogen-bond networks, and worked as a switch for the domain motions. Our results microscopically demonstrated the importance of hydrogen-bond networks of water molecules in understanding energy landscapes of protein motions.

Probing protein multidimensional conformational fluctuations by single-molecule multiparameter photon stamping spectroscopy.

Conformational motions of proteins are highly dynamic and intrinsically complex. To capture the temporal and spatial complexity of conformational motions and further to understand their roles in protein functions, an attempt is made to probe multidimensional conformational dynamics of proteins besides the typical one-dimensional FRET coordinate or the projected conformational motions on the one-dimensional FRET coordinate. T4 lysozyme hinge-bending motions between two domains along α-helix have been probed by single-molecule FRET. Nevertheless, the domain motions of T4 lysozyme are rather complex involving multiple coupled nuclear coordinates and most likely contain motions besides hinge-bending. It is highly likely that the multiple dimensional protein conformational motions beyond the typical enzymatic hinged-bending motions have profound impact on overall enzymatic functions. In this report, we have developed a single-molecule multiparameter photon stamping spectroscopy integrating fluorescence anisotropy, FRET, and fluorescence lifetime. This spectroscopic approach enables simultaneous observations of both FRET-related site-to-site conformational dynamics and molecular rotational (or orientational) motions of individual Cy3-Cy5 labeled T4 lysozyme molecules. We have further observed wide-distributed rotational flexibility along orientation coordinates by recording fluorescence anisotropy and simultaneously identified multiple intermediate conformational states along FRET coordinate by monitoring time-dependent donor lifetime, presenting a whole picture of multidimensional conformational dynamics in the process of T4 lysozyme open-close hinge-bending enzymatic turnover motions under enzymatic reaction conditions. By analyzing the autocorrelation functions of both lifetime and anisotropy trajectories, we have also observed the dynamic and static inhomogeneity of T4 lysozyme multidimensional conformational fluctuation dynamics, providing a fundamental understanding of the enzymatic reaction turnover dynamics associated with overall enzyme as well as the specific active-site conformational fluctuations that are not identifiable and resolvable in the conventional ensemble-averaged experiment.

Method of prediction and optimization of conformational motion of proteins based on mass transportation principle

The paper highlights approaches to fast prediction of protein conformational mobility. A new mathematical model based on the transportation principle is proposed. We describe an algorithm and soft-ware developed for a construction of the possible trajectories of the large-scale conformational motions of proteins (i.e. movements that occur within relatively large time intervals of the order of milliseconds). The modeling showed that the proposed method provides adequate, in terms of current knowledge of the biology and physics of proteins, results and allows simulation of large-scale conformational transitions for less time.

Nonlinearity of Mechanochemical Motions in Motor Proteins

The assumption of linear response of protein molecules to thermal noise or structural perturbations, such as ligand binding or detachment, is broadly used in the studies of protein dynamics. Conformational motions in proteins are traditionally analyzed in terms of normal modes and experimental data on thermal fluctuations in such macromolecules is also usually interpreted in terms of the excitation of normal modes. We have chosen two important protein motors — myosin V and kinesin KIF1A — and performed numerical investigations of their conformational relaxation properties within the coarse-grained elastic network approximation. We have found that the linearity assumption is deficient for ligand-induced conformational motions and can even be violated for characteristic thermal fluctuations. The deficiency is particularly pronounced in KIF1A where the normal mode description fails completely in describing functional mechanochemical motions. These results indicate that important assumptions of the theory of protein dynamics may need to be reconsidered. Neither a single normal mode nor a superposition of such modes yields an approximation of strongly nonlinear dynamics.

Complexity of aromatic ring-flip motions in proteins: Y97 ring dynamics in cytochrome c observed by cross-relaxation suppressed exchange NMR spectroscopy

Dynamics of large-amplitude conformational motions in proteins are complex and less understood, although these processes are intimately associated with structure, folding, stability, and function of proteins. Here, we use a large set of spectra obtained by cross-relaxation suppressed exchange NMR spectroscopy (EXSY) to study the 180 degrees flipping motion of the Y97 ring of horse ferricytochrome c as a function of near-physiological temperature in the 288-308 K range. With rising temperature, the ring-flip rate constant makes a continuous transition from Arrhenius to anti-Arrhenius behavior through a narrow Arrhenius-like zone. This behavior is seen not only for the native state of the protein, but also for native-like states generated by adding subdenaturing amounts of guanidine deuterochloride (GdnDCl). Moderately destabilizing concentrations of the denaturant (1.5 M GdnDCl) completely removes the Arrhenius-like feature from the temperature window employed. The Arrhenius to anti-Arrhenius transition can be explained by the heat capacity model where temperature strengthens ground state interactions, perhaps hydrophobic in nature. The effect of the denaturant may appear to arise from direct protein-denaturant interactions that are structure-stabilizing under subdenaturing conditions. The temperature distribution of rate constants under different stability conditions also suggests that the prefactor in Arrhenius-like relations is temperature dependent. Although the use of the transition state theory (TST) offers several challenges associated with data interpretation, the present results and a consideration of others published earlier provide evidence for complexity of ring-flip dynamics in proteins.

Can Principal Components Yield a Dimension Reduced Description of Protein Dynamics on Long Time Scales?

The suitability of principal component analysis (PCA) to yield slow collective coordinates for use within a dimension reduced description of conformational motions in proteins is evaluated. Two proteins are considered, T4 lysozyme and crambin. We present a quantitative evaluation of the convergence of conformational coordinates obtained with principal component analysis. Detailed analyses of (>200 ns) molecular dynamics trajectories and crystallographic data suggests that simulations of a few nanoseconds should generally provide a stable and statistically reliable definition of the essential and near constraints subspaces. Moreover, a systematic assessment of the density of states of the dynamics of all principal components showed that for an optimal separation of time scales it is crucial to include also side chain atoms in the PCA.

Collective Langevin dynamics of conformational motions in proteins

Functionally relevant slow conformational motions of proteins are, at present, in most cases inaccessible to molecular dynamics (MD) simulations. The main reason is that the major part of the computational effort is spend for the accurate description of a huge number of high frequency motions of the protein and the surrounding solvent. The accumulated influence of these fluctuations is crucial for a correct treatment of the conformational dynamics; however, their details can be considered irrelevant for most purposes. To accurately describe long time protein dynamics we here propose a reduced dimension approach, collective Langevin dynamics (CLD), which evolves the dynamics of the system within a small subspace of relevant collective degrees of freedom. The dynamics within the low-dimensional conformational subspace is evolved via a generalized Langevin equation which accounts for memory effects via memory kernels also extracted from short explicit MD simulations. To determine the memory kernel with differing levels of regularization, we propose and evaluate two methods. As a first test, CLD is applied to describe the conformational motion of the peptide neurotensin. A drastic dimension reduction is achieved by considering one single curved conformational coordinate. CLD yielded accurate thermodynamical and dynamical behaviors. In particular, the rate of transitions between two conformational states agreed well with a rate obtained from a 150 ns reference molecular dynamics simulation, despite the fact that the time scale of the transition (approximately 50 ns) was much longer than the 1 ns molecular dynamics simulation from which the memory kernel was extracted.

Measurement of intermediate exchange phenomena.

Understanding the crucial role of protein motions in the function of biological macromolecules requires methods for their characterization. These motions lead to noticeable alterations in the decay of nuclear spin magnetization. Recent advances in solution nuclear magnetic resonance (NMR) make quantitative connections between micro s-ms motions and nuclear spin relaxation in proteins. The techniques serve as useful probes of motional kinetics and thermodynamics and their relation to function. Here, we review the two most common experimental methods for characterizing conformational motions in proteins: the relaxation-compensated Carr-Purcell-Meiboom-Gill (rcCPMG) and off-resonance R1rho experiments.

Modeling the Correlation Functions of Conformational Motions in Proteins

A first principles calculation of the correlation function for conformational motion (CM) in proteins is carried out within the framework of a microscopic model of a protein as a heterogeneous system. The fragments of the protein are assumed to be identical hard spheres undergoing the CM within their conformational potentials about some mean equilibrium positions assigned by the tertiary structure. The memory friction function (MFF) for the generalized Langevin equation describing the CM of the particle is obtained on the basis of the direct calculation which is feasible for the present model of the protein due to the existence of a natural large parameter, viz. the ratio of the minimal distance between the mean equilibrium positions of the particles (∼7A) to the amplitude of their CM (<1A). A relationship between the MFF and the correlation functions of the CM of the particles is derived which makes their calculation to be a self-consistent mathematical problem. The general analysis of the MFF is exemplified by a simple model case in which the mean equilibrium positions of the particles form a regular lattice so that the correlation functions for all particles are the same. In this case the MFF is shown to be an infinite series of the powers of the auto-correlation function whose coefficients are independent on temperature. The latter is a result of the abstraction of the interaction potential by that of hard spheres which actually corresponds to the high temperature limit. On the examples of cubic and triangular lattices the coefficients are shown to be non-negative values which increase with the increase of the packing density of the particles and quickly tend to zero with the increase of their index. Thus the MFF can be approximated by a polynomial of the correlation function and the resulting mathematical equation is analogous to the one from the dynamic theory of liquids. The correlation function of the CM is obtained by numerical solution of the equation. At realistic packing densities for proteins it exhibits transparent non-exponential decay and includes two relaxation processes: the first one on the intermediate timescale (tens of picoseconds) and the second on the long timescale (its characteristic time is about tens of nanoseconds at small values of the friction coefficient and increases by orders of the magnitude with the increase of the latter). Thus the present approach provides the microscopic basis for previous phenomenologi- cal models of cooperative dynamics in proteins.

Predicting slow structural transitions in macromolecular systems: Conformational flooding.

We present a method to predict complex structural (conformational) transitions in irregular or disordered macromolecular systems, such as proteins or glasses, at the atomic level. Our method aims at rare events, which currently cannot be predicted with traditional molecular dynamics (MD) simulations, since these currently are limited to time scales shorter than a few nanoseconds. Given an initial conformation of the system, our method identifies one or more product states, which may be separated from the initial state by free energy barriers that are large on the scale of thermal energy. It also provides an approximate reaction path, which can be used to determine barrier heights or reaction rates with the usual techniques. The method employs an artificial potential that destabilizes the initial conformation and, thereby, lowers free energy barriers of structural transitions. As a result, transitions are accelerated and may be observed in MD simulations. An analytical estimate for the acceleration factor is given. The method is applied to two test systems, an argon microcluster and a simplified protein model. By these studies we demonstrated that our method is capable of shortening mean transition times from 0.5 \ensuremath{\mu}s (argon cluster) and 1.4 ns (protein model) to a few picoseconds. These results suggest that our method is particularly well suited to study biochemically relevant conformational motions in proteins at a microsecond time scale.

Spin-lattice relaxation and intramolecular motions in transferrin on the Mössbauer spectroscopy data

A new approach for the investigation of intramolecular motions in proteins, based on the study of spin-lattice relaxation of the iron atom of the protein active centres, has been developed. The gamma-resonance spectra have been obtained for the globules of transferrin enriched with57Fe. They possessed a paramagnetic hyperfine structure up to room temperature. This afforded the opportunity to experimentally investigate high temperature conformational motions in proteins and to study their influence on the spin-lattice relaxation. A theoretical model of relaxational spectra calculations has been developed, which enabled us to extract the frequency distribution of the spin-lattice relaxation from the shape of the spectra. The approach developed for the study of intramolecular dynamics of proteins based on the examination of spin-lattice relaxation in gamma-resonance spectra increases the frequency scale by at least one order in comparison with conventional methods.