NMR Structure Determination for Larger Proteins Using Backbone-Only Data

By Srivatsan Raman, Oliver F. Lange, P. Rossi, Michael D. Tyka, Xu Wang, J. Aramini, Gaohua Liu, T. Ramelot, A. Eletsky, Thomas Szyperski and 4 more. 2010

280 citations recorded by the source corpus.

Examining the Backbone Determination of tertiary protein structures by nuclear magnetic resonance (NMR) currently relies heavily on side-chain NMR data. The assignment of side-chain atoms is challenging. In addition, proteins larger than 15 kilodaltons (kD) must be deuterated to improve resolution and this eliminates the possibility of measuring long-range interproton distance constraints. Now Raman et al. (p. 1014, published online 4 February) use backbone-only NMR data—chemical shifts, residual dipolar coupling, and backbone amide proton distances—available from highly deuterated proteins to guide conformational searching in the Rosetta structure prediction protocol. Using this new protocol, they were able to generate accurate structures for proteins of up to 25 kD. Protein structures can be determined by using the limited nuclear magnetic resonance information obtainable for larger proteins. Conventional protein structure determination from nuclear magnetic resonance data relies heavily on side-chain proton-to-proton distances. The necessary side-chain resonance assignment, however, is labor intensive and prone to error. Here we show that structures can be accurately determined without nuclear magnetic resonance (NMR) information on the side chains for proteins up to 25 kilodaltons by incorporating backbone chemical shifts, residual dipolar couplings, and amide proton distances into the Rosetta protein structure modeling methodology. These data, which are too sparse for conventional methods, serve only to guide conformational search toward the lowest-energy conformations in the folding landscape; the details of the computed models are determined by the physical chemistry implicit in the Rosetta all-atom energy function. The new method is not hindered by the deuteration required to suppress nuclear relaxation processes for proteins greater than 15 kilodaltons and should enable routine NMR structure determination for larger proteins.

Subfields: Materials Chemistry, Molecular Biology, Spectroscopy

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Citations in the corpus

Critical Assessment of Methods of Protein Structure Prediction (CASP) – Progress and New directions in Round XI (2016, methodology): “28,29,32 In CASP11 we conducted an initial experiment to objectively assess the extent to which current modeling meth-ods can improve the accuracy of structures based on such data.”
Protein 3D Structure Computed from Evolutionary Sequence Variation (2011, methodology): “, by eliminating the need for heavy atom derivatives, by guiding the interpretation of electron density maps or by reducing the required number of experimental distance restraints, as elegantly demonstrated by the Baker and Montelione groups [77].”
Protein structure prediction from sequence variation (2012, background): “Such approaches have worked favorably in cases for smaller proteins that have fewer than ~90 amino acids 7 and need to be combined with experimental data for larger proteins 8,9 .”
High resolution comparative modeling with RosettaCM (2013, background): “…realistic all atom energy function to achieve atomic accuracy in many challenging structural biology problems, including structure determination with sparse experimental data and the design of new protein structures and interfaces(Fleishman et al., 2011; King et al., 2012; Raman et al., 2010).”
Systematic evaluation of CS‐Rosetta for membrane protein structure prediction with sparse NOE restraints (2017, background): “12 However, only a few long-distance restraints are usually sufficient to ensure convergence to the right structure.”
Protein Structure Determination from Pseudocontact Shifts Using ROSETTA (2012, methodology): “This bottleneck can potentially be avoided if methods for computing high-accuracy structures from backbone-only NMR experiments can be developed.(2) Pseudocontact shifts (PCSs) are a rich source of structural information that are manifested as large changes in chemical shifts in the NMR spectrum cau”
Accurate protein structure modeling using sparse NMR data and homologous structure information (2012, methodology): “Improved optimization with restraints suggests that the reduced conformational freedom, due to the use of restraints, is more than compensated by improved sampling nearer the low-energy native state (17).”
Serum Albumin Domain Structures in Human Blood Serum by Mass Spectrometry and Computational Biology (2015, background): “Further advancements that assist with protein structure determination have included the development of being able to use sparse NMR data, for example using backbone only data (7), and the understanding of evolutionary constraints for predicting protein structure (8).”
3D Protein Structure Predicted from Sequence (2011, unknown): “, by eliminating the need for heavy atom derivatives, by guiding the interpretation of electron density maps or by reducing the required number of experimental distance restraints, as elegantly demonstrated b”
Improvements to Robotics-Inspired Conformational Sampling in Rosetta (2013, background): “Many protein modeling protocols have an initial exploration stage, and the lowest-energy intermediates are then refined in multiple independent simulations in an intensified search for native-like minima [7,9].”