Langevin Network Model of Myosin

Miller, Benjamin; Zheng, Wenjun; Venable, Richard M.; Pastor, Richard W.; Brooks, Bernard R.

doi:10.1021/jp077042v

Cited by 18 publications

(29 citation statements)

References 30 publications

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“…Future studies should go beyond harmonic approximation and improve the modeling of other aspects of protein dynamics including anharmonicity 44 and solvent-damped diffusive motions. 45…”

Section: Discussionmentioning

confidence: 99%

All-atom modeling of anisotropic atomic fluctuations in protein crystal structures

Hafner

Zheng

2011

The Journal of Chemical Physics

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The accurate modeling of protein dynamics in crystalline states is essential for the development of computational techniques for simulating protein dynamics under physiological conditions. Following a previous coarse-grained modeling study of atomic fluctuations in protein crystal structures, we have refined our modeling with all-atom representation and force field. We have calculated the anisotropic atomic fluctuations of a protein structure interacting with its crystalline environment either explicitly (by including neighboring proteins into modeling) or implicitly (by adding harmonic restraints to surface atoms involved in crystal contacts). The modeling results are assessed in comparison with the experimental anisotropic displacement parameters (ADP) determined by X-ray crystallography. For a list of 40 high-resolution protein crystal structures, we have found that the optimal modeling of ADPs is achieved when the protein-environment interactions are much weaker than the internal interactions within a protein structure. Therefore, the intrinsic dynamics of a protein structure is only weakly perturbed by crystal packing. We have also found no noticeable improvement in the accuracy of ADP modeling by using all-atom over coarse-grained representation and force field, which justifies the use of coarse-grained modeling to investigate protein dynamics with both efficiency and accuracy.

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“…Future studies should go beyond harmonic approximation and improve the modeling of other aspects of protein dynamics including anharmonicity 44 and solvent-damped diffusive motions. 45…”

Section: Discussionmentioning

confidence: 99%

All-atom modeling of anisotropic atomic fluctuations in protein crystal structures

Hafner

Zheng

2011

The Journal of Chemical Physics

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“…Harmonic mechanical motions of the network of beads clearly do not incorporate dissipative dynamics of biomolecules in solution (34,45,46) and much is still needed to be done to achieve a physically consistent description of the protein dynamics. The elastic network employed here assigns weaker springs between all non-covalent neighbors within a cutoff radius and stronger springs between covalent neighbors.…”

Section: Discussionmentioning

confidence: 99%

Dissipative electro-elastic network model of protein electrostatics

2012

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We propose a dissipative electro-elastic network model to describe the dynamics and statistics of electrostatic fluctuations at active sites of proteins. The model combines the harmonic network of residue beads with overdamped dynamics of the normal modes of the network characterized by two friction coefficients. The electrostatic component is introduced to the model through atomic charges of the protein force field. The overall effect of the electrostatic fluctuations of the network is recorded through the frequency-dependent response functions of the electrostatic potential and electric field at the protein active site. We also consider the dynamics of displacements of individual residues in the network and the dynamics of distances between pairs of residues. The model is tested against loss spectra of residue displacements and the electrostatic potential and electric field at the heme's iron from all-atom molecular dynamics simulations of three hydrated globular proteins.

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“…Defining the 6N × 6N matrix (Miller et al 2008) 43) and the normal modes can be solved analytically by diagonalizing A. The first 3N components of the eigenvectors of A provide the displacements along the normal modes, and the last 3N components correspond to the mode velocities.…”

Section: Langevin Dynamicsmentioning

confidence: 99%

“…These models have been used to predict the global dynamics of a variety of proteins and protein complexes, ranging in size from single enzymes to macromolecular machines (Keskin et al 2002), ribosomes (Tama et al 2003, Wang et al 2004 and viral capsids (Tama & Brooks, 2002, Tama & Brooks, 2005. They have provided insights into a wide range of protein behaviors, such as mechanisms of allosteric regulation (Ming & Wall, 2005, Bahar et al 2007, Chennubhotla et al 2008, protein-protein binding (Tobi and Bahar 2005), anisotropic response to uniaxial tension and unfolding Bahar, 2008, Sulkowska et al 2008), colocalization of catalytic sites and key mechanical sites (e.g., hinges) (Yang & Bahar 2005), interactions at the binding sites (Ming & Wall, 2006), and energetics (Miller et al 2008), to name a few. ENMs allow the global motions of a molecule to be quickly calculated, making them an ideal complement to conventional molecular dynamics (MD) simulations.…”

Section: Introductionmentioning

confidence: 99%