Model-free methods of analyzing domain motions in proteins from simulation: A comparison of normal mode analysis and molecular dynamics simulation of lysozyme

Hayward, Steven; Kitao, Akio; Berendsen, Herman J. C.

doi:10.1002/(sici)1097-0134(199703)27:3<425::aid-prot10>3.0.co;2-n

Cited by 260 publications

(268 citation statements)

References 32 publications

Supporting

Mentioning

259

Contrasting

Unclassified

Order By: Relevance

“…This technique has the advantage that it is based on all-atom simulations, with the explicit damping forces and entropic contributions of the solvent, but the resulting modes can only be expressed by giving a 3N -component vector. Hayward et al [16] suggested specifying important modes a priori, and this provides us the great advantage being able to relate the results of several simulations together into a bigger picture. As long as our modes still contain the most important fluctuations, they are a reasonable basis to use.…”

Section: Resultsmentioning

confidence: 99%

Coarse-grained protein-protein stiffnesses and dynamics from all-atom simulations

Hicks

Henley

2010

Phys. Rev. E

View full text Add to dashboard Cite

Large protein assemblies, such as virus capsids, may be coarse-grained as a set of rigid domains linked by generalized (rotational and stretching) harmonic springs. We present a method to obtain the elastic parameters and overdamped dynamics for these springs from all-atom molecular dynamics simulations of one pair of domains at a time. The computed relaxation times of this pair give a consistency check for the simulation, and (using a fluctuation-dissipation relationship) we find the corrective force needed to null systematic drifts. As a first application we predict the stiffness of an HIV capsid layer and the relaxation time for its breathing mode. PACS numbers: 87.10.Pq,87.15.ap,87.15.hg,87.15.Ya Large protein assemblies-our particular interest is the capsids (shells) of viruses-are pertinent to most of the softmatter physics in cells; how can one calculate their elastic properties and corresponding dynamics? Such assemblies are too large to handle by all-atom simulations, but numerical coarse graining techniques are opening the door to direct simulations [1]. Nevertheless, we still prefer simplified parametrizations for the purposes of human understanding, analytic treatment, transmission to other researchers, and building up coarse-grained models [2]. In this paper we propose an approach to extract these simplified parameters from all-atom molecular dynamics (MD) of small subsystems.Assume we already know how to extract an appropriate subsystem and an intelligent way to project the 3N coordinates of its configurations onto s small number x. (Below, we do this explicitly for the case of the HIV capsid protein.) Our aim is, from the observed trajectories x(t), to extract the parameters for an effective Hamiltonian and equation of motion. We will model x(t) as an overdamped random walk in a biased harmonic potential. This walk is parametrized primarily by two important tensors: one to describe the shape of the harmonic well, and the other to describe the (mainly hydrodynamic) damping and the associated stochastic noise. Combining these tensors gives a matrix whose eigenvalues are the relaxation rates. With detailed measurement of the dynamics, we can identify whether the simulation is equilibrated during the simulation time, and can compute the external forces we must add so as to measure the behavior near the biologically proper configuration. This is similar in spirit to computing a potential of mean force or free energy landscape with Jarzynski's equality [3], except that our coarse-grained x has more than one component, and (at minimum) represents angular degrees of freedom in addition to stretching. As an application, we simulate the important inter-domain interactions in the HIV capsid and estimate the Young's modulus and Poisson ratio of the capsid lattice, as well as the relaxation rate of the breathing mode.Coarse graining as stochastic dynamics. We represent our system as a vector of generalized coordinates x i , i = 1 . . . N , where N is far smaller than the number of atoms and is obtained by s...

show abstract

Section: Resultsmentioning

confidence: 99%

Coarse-grained protein-protein stiffnesses and dynamics from all-atom simulations

Hicks

Henley

2010

Phys. Rev. E

View full text Add to dashboard Cite

show abstract

“…Along this common mode, the DYNDOM method (Hayward et al, 1997; identi®es two subdomains. The ®rst subdomain consists of residues 12-30, 37-83, 510-521 and the second subdomain of 32-34, 90-137, 411-506.…”

Section: Conformational Changes In the Equatorial Domainmentioning

confidence: 99%

“…Modes of collective¯uctuation were analysed for the presence of clear domain motions as described Hayward et al, 1997). This method analyses structural differences in terms of rigid body rotations.…”

Section: Dyndommentioning

confidence: 99%

Conformational changes in the chaperonin GroEL: new insights into the allosteric mechanism 1 1Edited by A. R. Fersht

Groot

Vriend

Berendsen

1999

Journal of Molecular Biology

View full text Add to dashboard Cite

Conformational changes are known to play a crucial role in the function of the bacterial GroE chaperonin system. Here, results are presented from an essential dynamics analysis of known experimental structures and from computer simulations of GroEL using the CONCOORD method. The results indicate a possible direct form of inter-ring communication associated with internal¯uctuations in the nucleotide-binding domains upon nucleotide and GroES binding that are involved in the allosteric mechanism of GroEL. At the level of conformational transitions in entire GroEL rings, nucleotide-induced structural changes were found to be distinct and in principle uncoupled from changes occurring upon GroES binding. However, a coupling is found between nucleotide-induced conformational changes and GroES-mediated transitions, but only in simulations of GroEL double rings, and not in simulations of single rings. This provides another explanation for the fact that GroEL functions a double ring system.

show abstract

“…Furthermore, the trajectory of protein motion will rarely be in a straight line, and therefore an otherwise correctly predicted initial direction of motion might deviate noticeably from the observed conformational change (22). Despite these limitations, many studies have found agreement between features of the motion predicted by NMA and the observed or simulated conformational change of one or a small number of proteins (23)(24)(25)(26)(27)(28)(29)(30). A number of large-scale studies have assessed the success of normal modes at describing protein motion as defined by the database of macromolecular movements (31).…”

mentioning

confidence: 99%

Insights into protein flexibility: The relationship between normal modes and conformational change upon protein–protein docking

Dobbins

Lesk²,

Sternberg³

2008

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

208

216

View full text Add to dashboard Cite

Understanding protein interactions has broad implications for the mechanism of recognition, protein design, and assigning putative functions to uncharacterized proteins. Studying protein flexibility is a key component in the challenge of describing protein interactions. In this work, we characterize the observed conformational change for a set of 20 proteins that undergo large conformational change upon association (>2 Å C␣ RMSD) and ask what features of the motion are successfully reproduced by the normal modes of the system. We demonstrate that normal modes can be used to identify mobile regions and, in some proteins, to reproduce the direction of conformational change. In 35% of the proteins studied, a single low-frequency normal mode was found that describes well the direction of the observed conformational change. Finally, we find that for a set of 134 proteins from a docking benchmark that the characteristic frequencies of normal modes can be used to predict reliably the extent of observed conformational change. We discuss the implications of the results for the mechanics of protein recognition.conformational selection ͉ elastic network model ͉ induced fit ͉ protein interactions ͉ protein recognition P roteins are not static, and many undergo substantial rearrangements upon binding to other molecules (1). Such changes are central to protein function (2). The limitations of our understanding of conformational change impact markedly on our ability to model such changes. A successful approach to modeling protein flexibility, one of the key current challenges in developing protein-protein docking algorithms, would have far-reaching consequences for the fields of drug design and function prediction.The initial lock-and-key description of protein interaction, first introduced by Fischer in 1894 (3), did not account for conformational change and has since been modified, beginning with Koshland's induced fit hypothesis in 1958 (4). However, a range of studies including molecular dynamics (picosecondnanosecond time scales), NMR, and single-molecule FRET experiments (microsecond-millisecond time scales) (5-7), have questioned the extent to which conformational change can be considered induced by the binding partner.An alternative mechanism is conformational selection, where the native state of the protein exists in an ensemble of conformations, with the partner binding selectively to a specific conformation, thus shifting the equilibrium toward the binding conformation (8). An elaboration, proposed by Grunberg et al. (9), describes a three-stage process consisting of (i) independent diffusion of the receptor and ligand each subject to conformational fluctuations, (ii) an encounter between the receptor and ligand leading to a series of microcollisions that may result in the formation of a recognition complex, and (iii) either dissociation of the encounter complex or formation of the bound complex with possible further conformational changes resulting from induced fit. An important question to address is, therefore, ...

show abstract

Model-free methods of analyzing domain motions in proteins from simulation: A comparison of normal mode analysis and molecular dynamics simulation of lysozyme

Cited by 260 publications

References 32 publications

Coarse-grained protein-protein stiffnesses and dynamics from all-atom simulations

Coarse-grained protein-protein stiffnesses and dynamics from all-atom simulations

Conformational changes in the chaperonin GroEL: new insights into the allosteric mechanism 1 1Edited by A. R. Fersht

Insights into protein flexibility: The relationship between normal modes and conformational change upon protein–protein docking

Contact Info

Product

Resources

About