Protein normal-mode dynamics: Trypsin inhibitor, crambin, ribonuclease and lysozyme

Levitt, Michael; Sander, Christian; Stern, Peter

doi:10.1016/0022-2836(85)90230-x

Cited by 699 publications

(597 citation statements)

References 33 publications

Supporting

Mentioning

578

Contrasting

Unclassified

Order By: Relevance

“…Oscillations between larger (1-1.1/~) and smaller (0.75/~) rms distances occur also at intervals of 200 ps. Normal mode analyses of the protein dynamics shows the lowest harmonic frequency modes to have periods of the order of a few ps [47,48]. Therefore the motions responsible for the oscillations seen here must originate from non harmonic collective long-range behavior.…”

Section: Time Evolution Of the Distance Between Configurationsmentioning

confidence: 71%

Multi-basin dynamics of a protein in a crystal environment

Garcı́a

Blumenfeld

Hummer

et al. 1997

Physica D: Nonlinear Phenomena

View full text Add to dashboard Cite

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.

show abstract

Section: Time Evolution Of the Distance Between Configurationsmentioning

confidence: 71%

Multi-basin dynamics of a protein in a crystal environment

Garcı́a

Blumenfeld

Hummer

et al. 1997

Physica D: Nonlinear Phenomena

View full text Add to dashboard Cite

show abstract

“…However, the dynamics of large proteins typically occurs at time scales that are intractable to MD simulations. Alternative approaches have also been developed in the past few decades, including normal mode analysis (NMA), 8,25,36,55 elastic network model (ENM), 58 Gaussian network model (GNM), 5,6,22 and anisotropic network model (ANM). 4 In fact, these methods can be regarded as time-independent molecular mechanics (MM) and are connected to MD methods via the timeharmonic approximation.…”

Section: Introductionmentioning

confidence: 99%

“…Such lowenergy eigenvalues reflect the long-time behavior of the protein dynamics beyond the reach of MD simulations. 6,8,36,55,58 These approaches have been improved in many aspects including crystal periodicity corrections 28,34,35,54 and densitycluster rotational-translational blocking. 20 These methods are relatively inexpensive particularly in their coarse-grained settings.…”

Section: Introductionmentioning

confidence: 99%

Multiscale multiphysics and multidomain models—Flexibility and rigidity

Xia

Opron

Guo

2013

The Journal of Chemical Physics

221

View full text Add to dashboard Cite

The emerging complexity of large macromolecules has led to challenges in their full scale theoretical description and computer simulation. Multiscale multiphysics and multidomain models have been introduced to reduce the number of degrees of freedom while maintaining modeling accuracy and achieving computational efficiency. A total energy functional is constructed to put energies for polar and nonpolar solvation, chemical potential, fluid flow, molecular mechanics, and elastic dynamics on an equal footing. The variational principle is utilized to derive coupled governing equations for the above mentioned multiphysical descriptions. Among these governing equations is the PoissonBoltzmann equation which describes continuum electrostatics with atomic charges. The present work introduces the theory of continuum elasticity with atomic rigidity (CEWAR). The essence of CE-WAR is to formulate the shear modulus as a continuous function of atomic rigidity. As a result, the dynamics complexity of a macromolecular system is separated from its static complexity so that the more time-consuming dynamics is handled with continuum elasticity theory, while the less time-consuming static analysis is pursued with atomic approaches. We propose a simple method, flexibility-rigidity index (FRI), to analyze macromolecular flexibility and rigidity in atomic detail. The construction of FRI relies on the fundamental assumption that protein functions, such as flexibility, rigidity, and energy, are entirely determined by the structure of the protein and its environment, although the structure is in turn determined by all the interactions. As such, the FRI measures the topological connectivity of protein atoms or residues and characterizes the geometric compactness of the protein structure. As a consequence, the FRI does not resort to the interaction Hamiltonian and bypasses matrix diagonalization, which underpins most other flexibility analysis methods. FRI's computational complexity is of O(N 2 ) at most, where N is the number of atoms or residues, in contrast to O(N 3 ) for Hamiltonian based methods. We demonstrate that the proposed FRI gives rise to accurate prediction of protein B-Factor for a set of 263 proteins. We show that a parameter free FRI is able to achieve about 95% accuracy of the parameter optimized FRI. An interpolation algorithm is developed to construct continuous atomic flexibility functions for visualization and use with CEWAR.

show abstract

“…Although at first sight, the conformational selection paradigm and the approach that we used in this study look different, the similarity between them becomes clear if we make an analogy between "discrete breathers" and the eigenmodes of the burial mode model energy function 12 -in both descriptions, ligand-binding suppresses one mode and stimulates another, coupling large scale motions to the transduction of small forces. Furthermore, it should be noted in passing that, unlike methods which use the normal mode analysis to compute structural variability and mechanical response, [32][33][34][35] burial mode analysis relies only on sequence information and is not limited to small perturbations about a local energy minimum in a particular conformational state. Thus, burial mode analysis may yet prove useful as a general tool for prediction of catalytic and ligand-binding sites from primary sequence information.…”

Section: Discussionmentioning

confidence: 99%

Quantitative theory of hydrophobic effect as a driving force of protein structure

Perunov

England

2014

Protein Science

View full text Add to dashboard Cite

Various studies suggest that the hydrophobic effect plays a major role in driving the folding of proteins. In the past, however, it has been challenging to translate this understanding into a predictive, quantitative theory of how the full pattern of sequence hydrophobicity in a protein shapes functionally important features of its tertiary structure. Here, we extend and apply such a phenomenological theory of the sequence-structure relationship in globular protein domains, which had previously been applied to the study of allosteric motion. In an effort to optimize parameters for the model, we first analyze the patterns of backbone burial found in singledomain crystal structures, and discover that classic hydrophobicity scales derived from bulk physicochemical properties of amino acids are already nearly optimal for prediction of burial using the model. Subsequently, we apply the model to studying structural fluctuations in proteins and establish a means of identifying ligand-binding and protein-protein interaction sites using this approach.

show abstract

Protein normal-mode dynamics: Trypsin inhibitor, crambin, ribonuclease and lysozyme

Cited by 699 publications

References 33 publications

Multi-basin dynamics of a protein in a crystal environment

Multi-basin dynamics of a protein in a crystal environment

Multiscale multiphysics and multidomain models—Flexibility and rigidity

Quantitative theory of hydrophobic effect as a driving force of protein structure

Contact Info

Product

Resources

About