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A B-factor for NOEs?
(2022)
Nuclear Overhauser effects (NOEs) are influenced by motion. Here, we derive exact, analytical results for a model of isotropic, harmonic fluctuations of atom positions that corresponds to the one underlying crystallographic B-factors. The model includes steric repulsion and yields closed-form expressions for the expected value of general invertible functions of the distance between two atoms, with the special case r-6 for NOEs. We discuss the implications for the definition of an NOE-based B-factor in solution NMR.
The three-dimensional structure determination of RNAs by NMR spectroscopy relies on chemical shift assignment, which still constitutes a bottleneck. In order to develop more efficient assignment strategies, we analysed relationships between sequence and 1H and 13C chemical shifts. Statistics of resonances from regularly Watson– Crick base-paired RNA revealed highly characteristic chemical shift clusters. We developed two approaches using these statistics for chemical shift assignment of double-stranded RNA (dsRNA): a manual approach that yields starting points for resonance assignment and simplifies decision trees and an automated approach based on the recently introduced automated resonance assignment algorithm FLYA. Both strategies require only unlabeled RNAs and three 2D spectra for assigning the H2/C2, H5/C5, H6/C6, H8/C8 and H10/C10 chemical shifts. The manual approach proved to be efficient and robust when applied to the experimental data of RNAs with a size between 20 nt and 42 nt. The more advanced automated assignment approach was successfully applied to four stemloop RNAs and a 42 nt siRNA, assigning 92–100% of the resonances from dsRNA regions correctly. This is the first automated approach for chemical shift assignment of non-exchangeable protons of RNA and their corresponding 13C resonances, which provides an important step toward automated structure determination of RNAs.
Resonance assignments are challenging for membrane proteins due to the size of the lipid/detergent-protein complex and the presence of line-broadening from conformational exchange. As a consequence, many correlations are missing in the triple-resonance NMR experiments typically used for assignments. Herein, we present an approach in which correlations from these solution-state NMR experiments are supplemented by data from 13C unlabeling, single-amino acid type labeling, 4D NOESY data and proximity of moieties to lipids or water in combination with a structure of the protein. These additional data are used to edit the expected peaklists for the automated assignment protocol FLYA, a module of the program package CYANA. We demonstrate application of the protocol to the 262-residue proton pump from archaeal bacteriorhodopsin (bR) in lipid nanodiscs. The lipid-protein assembly is characterized by an overall correlation time of 44 ns. The protocol yielded assignments for 62% of all backbone (H, N, Cα, Cβ, C′) resonances of bR, corresponding to 74% of all observed backbone spin systems, and 60% of the Ala, Met, Ile (δ1), Leu and Val methyl groups, thus enabling to assign a large fraction of the protein without mutagenesis data. Most missing resonances stem from the extracellular half, likely due intermediate exchange line-broadening. Further analysis revealed that missing information of the amino acid type of the preceding residue is the largest problem, and that 4D NOESY experiments are particularly helpful to compensate for that information loss.
We compiled an NMR data set consisting of exact nuclear Overhauser enhancement (eNOE) distance limits, residual dipolar couplings (RDCs) and scalar (J) couplings for GB3, which forms one of the largest and most diverse data set for structural characterization of a protein to date. All data have small experimental errors, which are carefully estimated. We use the data in the research article Vogeli et al., 2015, Complementarity and congruence between exact NOEs and traditional NMR probes for spatial decoding of protein dynamics, J. Struct. Biol., 191, 3, 306–317, doi:10.1016/j.jsb.2015.07.008 [1] for cross-validation in multiple-state structural ensemble calculation. We advocate this set to be an ideal test case for molecular dynamics simulations and structure calculations.
Adequate digital resolution and signal sensitivity are two critical factors for protein structure determinations by solution NMR spectroscopy. The prime objective for obtaining high digital resolution is to resolve peak overlap, especially in NOESY spectra with thousands of signals where the signal analysis needs to be performed on a large scale. Achieving maximum digital resolution is usually limited by the practically available measurement time. We developed a method utilizing non-uniform sampling for balancing digital resolution and signal sensitivity, and performed a large-scale analysis of the effect of the digital resolution on the accuracy of the resulting protein structures. Structure calculations were performed as a function of digital resolution for about 400 proteins with molecular sizes ranging between 5 and 33 kDa. The structural accuracy was assessed by atomic coordinate RMSD values from the reference structures of the proteins. In addition, we monitored also the number of assigned NOESY cross peaks, the average signal sensitivity, and the chemical shift spectral overlap. We show that high resolution is equally important for proteins of every molecular size. The chemical shift spectral overlap depends strongly on the corresponding spectral digital resolution. Thus, knowing the extent of overlap can be a predictor of the resulting structural accuracy. Our results show that for every molecular size a minimal digital resolution, corresponding to the natural linewidth, needs to be achieved for obtaining the highest accuracy possible for the given protein size using state-of-the-art automated NOESY assignment and structure calculation methods.
Global response of diacylglycerol kinase towards substrate binding observed by 2D and 3D MAS NMR
(2019)
Escherichia coli diacylglycerol kinase (DGK) is an integral membrane protein, which catalyses the ATP-dependent phosphorylation of diacylglycerol (DAG) to phosphatic acid (PA). It is a unique trimeric enzyme, which does not share sequence homology with typical kinases. It exhibits a notable complexity in structure and function despite of its small size. Here, chemical shift assignment of wild-type DGK within lipid bilayers was carried out based on 3D MAS NMR, utilizing manual and automatic analysis protocols. Upon nucleotide binding, extensive chemical shift perturbations could be observed. These data provide evidence for a symmetric DGK trimer with all of its three active sites concurrently occupied. Additionally, we could detect that the nucleotide substrate induces a substantial conformational change, most likely directing DGK into its catalytic active form. Furthermore, functionally relevant interprotomer interactions are identified by DNP-enhanced MAS NMR in combination with site-directed mutagenesis and functional assays.
RNA not only translates the genetic code into proteins, but also carries out important cellular functions. Understanding such functions requires knowledge of the structure and dynamics at atomic resolution. Almost half of the published RNA structures have been solved by nuclear magnetic resonance (NMR). However, as a result of severe resonance overlap and low proton density, high-resolution RNA structures are rarely obtained from nuclear Overhauser enhancement (NOE) data alone. Instead, additional semi-empirical restraints and labor-intensive techniques are required for structural averages, while there are only a few experimentally derived ensembles representing dynamics. Here we show that our exact NOE (eNOE) based structure determination protocol is able to define a 14-mer UUCG tetraloop structure at high resolution without other restraints. Additionally, we use eNOEs to calculate a two-state structure, which samples its conformational space. The protocol may open an avenue to obtain high-resolution structures of small RNA of unprecedented accuracy with moderate experimental efforts.
The YaeJ protein is a codon-independent release factor with peptidyl-tRNA hydrolysis (PTH) activity, and functions as a stalled-ribosome rescue factor in Escherichia coli. To identify residues required for YaeJ function, we performed mutational analysis for in vitro PTH activity towards rescue of ribosomes stalled on a non-stop mRNA, and for ribosome-binding efficiency. We focused on residues conserved among bacterial YaeJ proteins. Additionally, we determined the solution structure of the GGQ domain of YaeJ from E. coli using nuclear magnetic resonance spectroscopy. YaeJ and a human homolog, ICT1, had similar levels of PTH activity, despite various differences in sequence and structure. While no YaeJ-specific residues important for PTH activity occur in the structured GGQ domain, Arg118, Leu119, Lys122, Lys129 and Arg132 in the following C-terminal extension were required for PTH activity. All of these residues are completely conserved among bacteria. The equivalent residues were also found in the C-terminal extension of ICT1, allowing an appropriate sequence alignment between YaeJ and ICT1 proteins from various species. Single amino acid substitutions for each of these residues significantly decreased ribosome-binding efficiency. These biochemical findings provide clues to understanding how YaeJ enters the A-site of stalled ribosomes.
Investigating three-dimensional (3D) structures of proteins in living cells by in-cell nuclear magnetic resonance (NMR) spectroscopy opens an avenue towards understanding the structural basis of their functions and physical properties under physiological conditions inside cells. In-cell NMR provides data at atomic resolution non-invasively, and has been used to detect protein-protein interactions, thermodynamics of protein stability, the behavior of intrinsically disordered proteins, etc. in cells. However, so far only a single de novo 3D protein structure could be determined based on data derived only from in-cell NMR. Here we introduce methods that enable in-cell NMR protein structure determination for a larger number of proteins at concentrations that approach physiological ones. The new methods comprise (1) advances in the processing of non-uniformly sampled NMR data, which reduces the measurement time for the intrinsically short-lived in-cell NMR samples, (2) automatic chemical shift assignment for obtaining an optimal resonance assignment, and (3) structure refinement with Bayesian inference, which makes it possible to calculate accurate 3D protein structures from sparse data sets of conformational restraints. As an example application we determined the structure of the B1 domain of protein G at about 250 μM concentration in living E. coli cells.
1H-detected solid-state NMR experiments feasible at fast magic-angle spinning (MAS) frequencies allow accessing 1H chemical shifts of proteins in solids, which enables their interpretation in terms of secondary structure. Here we present 1H and 13C-detected NMR spectra of the RNA polymerase subunit Rpo7 in complex with unlabeled Rpo4 and use the 13C, 15N, and 1H chemical-shift values deduced from them to study the secondary structure of the protein in comparison to a known crystal structure. We applied the automated resonance assignment approach FLYA including 1H-detected solid-state NMR spectra and show its success in comparison to manual spectral assignment. Our results show that reasonably reliable secondary-structure information can be obtained from 1H secondary chemical shifts (SCS) alone by using the sum of 1Hα and 1HN SCS rather than by TALOS. The confidence, especially at the boundaries of the observed secondary structure elements, is found to increase when evaluating 13C chemical shifts, here either by using TALOS or in terms of 13C SCS.