Limits on Variations in Protein Backbone Dynamics from Precise Measurements of Scalar Couplings

Abstract

3JHN,Halpha, 3JHN,Cbeta, and 3JHN,C' couplings, all related to the backbone torsion angle phi, were measured for the third immunoglobulin binding domain of protein G, or GB3. Measurements were carried out using both previously published methods and novel sequences based on the multiple-quantum principle, which limit attenuation of experimental couplings caused by finite lifetimes of the spin states of passive spins. High reproducibility between the multiple-quantum and conventional approaches confirms the accuracy of the measurements. With few exceptions, close agreement between 3JHN,Halpha, 3JHN,Cbeta, and 3JHN,C' and values predicted by their respective Karplus equations is observed. For the three types of couplings, up to 20% better agreement is obtained when fitting the experimental couplings to a dynamic ensemble NMR structure, which has a phi angle root-mean-square spread of 9 +/- 4 degrees and was previously calculated on the basis of a very extensive set of residual dipolar couplings, than for any single static NMR structure. Fits of 3J couplings to a 1.1-A X-ray structure, with hydrogens added in idealized positions, are 40-90% worse. Approximately half of the improvement when fitting to the NMR structures relates to the amide proton deviating from its idealized, in-peptide-plane position, indicating that the positioning of hydrogens relative to the backbone atoms is one of the factors limiting the accuracy at which the backbone torsion angle phi can be extracted from 3J couplings. Introducing an additional, residue-specific variable for the amplitude of phi angle fluctuations does not yield a statistically significant improvement when fitting to a set of dynamic Karplus curves, pointing to a homogeneous behavior of these amplitudes.

The nuclear Overhauser effect from a quantitative perspective

“…Still the ensemble embodies low-amplitude, high-probability, anisotropic motion in the backbone on the picosecond to nanosecond time regime. NMR observables predicted from the ensemble were in excellent agreement with independently measured, highly accurate data such as backbone H-H RDCs and scalar couplings [196,197].…”

Bayesian Energy Landscape Tilting: Towards Concordant Models of Molecular Ensembles

“…The J couplings were calculated using the following Karplus relations: (20). J coupling uncertainties were approximated as the RMS errors reported when fitting the Karplus coefficients.…”

Assessing and refining molecular dynamics simulations of proteins with nuclear magnetic resonance data

“…More sophisticated fitting methods such as Bayesian inference have also been used (Habeck et al 2005). Efforts have been made to incorporate the effects of dynamics and averaging into the parameters by self-consistent fitting (Schmidt et al 1999;Pérez et al 2001) and by deriving the parameters from ensembles of structures obtained from MD simulations (Brüschweiler and Case 1994;Lindorff-Larsen et al 2005b;Vögeli et al 2007), but such parameters are not necessarily transferable. When the Karplus relation is used, its approximate form and parameters mean that 3 J-couplings should be interpreted with an uncertainty of at least ±1 Hz (Allison and van Gunsteren 2009;Steiner et al 2012).…”