Correlation Times and Adiabatic Barriers for Methyl Rotation in SNase

Chatfield, David C.; Augsten, Alberto; D’Cunha, Cassian

doi:10.1023/b:jnmr.0000032553.13686.0b

Cited by 20 publications

(49 citation statements)

References 12 publications

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“…Likewise, in FNfn10, the methyl groups of the buried V72 and solvent-exposed V45 have similar rotation rates (residence times 95 ps and 126 ps). Chatfield et al found that steric (van der Waals) interactions with neighbouring residues were most important in determining methyl rotation rates, 33 and that a Boltzmann weighted average of the adiabatic energy barriers calculated from different structures from an MD simulation was able to predict methyl correlation times quite well, 42 in accord with earlier results. 43 Indeed, a simple calculation of barriers from rigid rotation about the dihedral angle shows that the buried methyl groups that are rotating rapidly do not have significant barriers to rotation arising from van der Waals interactions.…”

Section: Methyl and Side-chain Rotameric Transitionsmentioning

confidence: 58%

What Contributions to Protein Side-chain Dynamics are Probed by NMR Experiments? A Molecular Dynamics Simulation Analysis

Best¹,

Clarke²,

Karplus

2005

Journal of Molecular Biology

154

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Section: Methyl and Side-chain Rotameric Transitionsmentioning

confidence: 58%

What Contributions to Protein Side-chain Dynamics are Probed by NMR Experiments? A Molecular Dynamics Simulation Analysis

Best¹,

Clarke²,

Karplus

2005

Journal of Molecular Biology

154

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“…15,22 The rmsd of 0.06 between experimental and simulated J(0) values is smaller than the rmsd between the experimental J(0) of the Ca 2+ -bound and the apo state. The largest discrepancy is found for Thr45 (boxed data point) whose time correlation function is not wellconverged; 3 that is, its S 2 value has a low precision (see Supporting Information).…”

Section: C(t) ) E -T/τ C C Cc (T)c Ch 3 (T)mentioning

confidence: 78%

Toward Quantitative Interpretation of Methyl Side-Chain Dynamics from NMR by Molecular Dynamics Simulations

et al. 2007

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Advances in molecular dynamics (MD) force fields 1-3 have recently allowed the nearly quantitative interpretation of protein backbone dynamics as measured by NMR spin relaxation 4,5 and residual dipolar couplings. 6 These improvements were solely due to modification of the backbone ,ψ dihedral angle potential, as implemented in the AMBER99SB 2 and CHARMM22/CMAP 1 force fields. Amino acid side-chain motions, on the other hand, often play an important functional role, but their accurate simulation has been a considerable challenge in the past. [7][8][9] Because changes in side-chain motions are not necessarily correlated to changes in protein backbone mobility, 10 it is unclear how these force-field modifications affect side-chain dynamics. Here, we compare experimental and simulated side-chain NMR relaxation parameters of calbindin D 9k and ubiquitin and report significant improvements in the quantitative representation of sidechain motions by computation.Methyl groups are the dynamically best studied side-chain moieties of proteins. 9-15 Deuterium relaxation experiments of 13 CH 2 D methyl groups report on picosecond-nanosecond dynamics and measure up to five different relaxation rates for each methyl group at a given B 0 field. 14 They allow the unambiguous extraction of spectral densities J(0), J(ω D ), and J(2ω D ), where ω D is the Larmor frequency of deuterium. As shown here, these spectral densities lend themselves to direct comparison with computer simulations ( Figure 1). Alternatively, model-free dynamics parameters 14,16,17 can be determined from the experiment first and compared with the corresponding simulated parameters (Figure 2).Methyl side-chain dynamics of calbindin in its calcium-bound form have recently been reported. 18 Up to five spectral densities J(ω) have been determined for each of the 37 analyzable methyl groups and interpreted in terms of a model-free analysis.Here, a 50 ns MD simulation of Ca 2+ -bound calbindin (PDB entry 3ICB 19 with the mutation P34M) was performed using the AMBER 8 20 simulation program with the parameter set AMBER99SB following the protocol described previously. 4 The starting configuration was generated by immersing the calbindin structure in a cubic box with 5778 explicit SPC water molecules and neutralizing counterions. Production dynamics were run at 300 K and 1 atm pressure, with snapshots saved every 1 ps.The spectral densities J(ω) ) ∫ -∞ ∞ C(t)cos(ωt)dt are backcalculated from the trajectory by using the following parametrization of the reorientational time-correlation function C(t) of the methyl C-H bond vectors:where τ c is the experimentally determined overall tumbling correlation time, C CC (t) is the reorientational correlation function of the C-C bond that connects the methyl group with the rest of the protein, and C CH3 (t) is the correlation function describing the methyl group rotation itself. Equation 1, which is a modification of the extended model-free approach, 17,21 factors C(t) into three parts by assuming statistical independence between C-...

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“…Such eigenmodes are also missing in MF calculations yielding inaccurate τ e values. There are reports in the literature that τ e MF is often too small [269]. …”

Section: Appendicesmentioning

confidence: 99%

Structural dynamics of bio-macromolecules by NMR: The slowly relaxing local structure approach

Meirovitch

Shapiro

Polimeno

et al. 2010

Progress in Nuclear Magnetic Resonance Spectroscopy

305

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Protein dynamics by NMR has been reviewed extensively in recent years. These surveys show decisively that information on structure should be complemented by information on motion both to properly characterize the protein, and to understand its function. The time scale accessible by NMR extends from picoseconds to days, with different methods accessing different parts of this time axis. Here we focus on heteronuclear NMR spin relaxation used to study ps to ns protein dynamics. The slow limit of this time regime is determined by the global tumbling of the protein, with the rates for internal motion of the probe being typically faster. Based on experience gained over nearly a decade we came to the conclusion that the traditional method of NMR spin relaxation analysis in proteins and nucleic acids, called “model-free” (MF), does not extract adequately and fully the information inherent in the experimental data largely because it is oversimplified. We have developed an approach that overcomes many of the MF deficiencies. This method, called the slowly relaxing local structure (SRLS) may be regarded as a generalization of MF. SRLS predates the MF approach, and even provided derivations of the exact equivalents of the MF equations . The issues brought up above will be addressed in detail in this review. It will be shown that analogous, but physically distinct, SRLS and MF analyses often yield substantially different results, indicating that the oversimplifications inherent in MF have unfavorable practical implications. Within a broader perspective, we illustrate the disadvantages of applying parameterization instead of setting forth models, using mathematical instead of physical parameter definitions, and not abiding by the assumptions underlying the various equations used. We offer the concepts that underlie SRLS as an alternative to the model-free point-of-view, and we describe and illustrate how SRLS can be implemented in a practical fashion. We also indicate how improvements to the current SRLS approach can be introduced

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Correlation Times and Adiabatic Barriers for Methyl Rotation in SNase

Cited by 20 publications

References 12 publications

What Contributions to Protein Side-chain Dynamics are Probed by NMR Experiments? A Molecular Dynamics Simulation Analysis

What Contributions to Protein Side-chain Dynamics are Probed by NMR Experiments? A Molecular Dynamics Simulation Analysis

Toward Quantitative Interpretation of Methyl Side-Chain Dynamics from NMR by Molecular Dynamics Simulations

Structural dynamics of bio-macromolecules by NMR: The slowly relaxing local structure approach

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