Nuclear Magnetic Resonance Structure Determination Research Articles

Recent Advances in NMR Protein Structure Prediction with ROSETTA.

Nuclear magnetic resonance (NMR) spectroscopy is a powerful method for studying the structure and dynamics of proteins in their native state. For high-resolution NMR structure determination, the collection of a rich restraint dataset is necessary. This can be difficult to achieve for proteins with high molecular weight or a complex architecture. Computational modeling techniques can complement sparse NMR datasets (<1 restraint per residue) with additional structural information to elucidate protein structures in these difficult cases. The Rosetta software for protein structure modeling and design is used by structural biologists for structure determination tasks in which limited experimental data is available. This review gives an overview of the computational protocols available in the Rosetta framework for modeling protein structures from NMR data. We explain the computational algorithms used for the integration of different NMR data types in Rosetta. We also highlight new developments, including modeling tools for data from paramagnetic NMR and hydrogen-deuterium exchange, as well as chemical shifts in CS-Rosetta. Furthermore, strategies are discussed to complement and improve structure predictions made by the current state-of-the-art AlphaFold2 program using NMR-guided Rosetta modeling.

Pmu1a, a novel spider toxin with dual inhibitory activity at pain targets hNaV 1.7 and hCaV 3 voltage-gated channels.

Venom-derived peptides targeting ion channels involved in pain are regarded as a promising alternative to current, and often ineffective, chronic pain treatments. Many peptide toxins are known to specifically and potently block established therapeutic targets, among which the voltage-gated sodium and calcium channels are major contributors. Here, we report on the discovery and characterization of a novel spider toxin isolated from the crude venom of Pterinochilus murinus that shows inhibitory activity at both hNaV 1.7 and hCaV 3.2 channels, two therapeutic targets implicated in pain pathways. Bioassay-guided HPLC fractionation revealed a 36-amino acid peptide with three disulfide bridges named μ/ω-theraphotoxin-Pmu1a (Pmu1a). Following isolation and characterization, the toxin was chemically synthesized, and its biological activity was further assessed using electrophysiology, revealing Pmu1a to be a toxin that potently blocks both hNaV 1.7 and hCaV 3. NMR structure determination of Pmu1a shows an inhibitor cystine knot (ICK) fold that is characteristic of many spider peptides. Combined, these data show the potential of Pmu1a as a basis for the design of compounds with dual activity at the therapeutically relevant hCaV 3.2 and hNaV 1.7 voltage-gated channels.

A mechanism of platelet integrin αIIbβ3 outside-in signaling through a novel integrin αIIb subunit–filamin–actin linkage

AbstractThe communication of talin-activated integrin αIIbβ3 with the cytoskeleton (integrin outside-in signaling) is essential for platelet aggregation, wound healing, and hemostasis. Filamin, a large actin crosslinker and integrin binding partner critical for cell spreading and migration, is implicated as a key regulator of integrin outside-in signaling. However, the current dogma is that filamin, which stabilizes inactive αIIbβ3, is displaced from αIIbβ3 by talin to promote the integrin activation (inside-out signaling), and how filamin further functions remains unresolved. Here, we show that while associating with the inactive αIIbβ3, filamin also associates with the talin-bound active αIIbβ3 to mediate platelet spreading. Fluorescence resonance energy transfer–based analysis reveals that while associating with both αIIb and β3 cytoplasmic tails (CTs) to maintain the inactive αIIbβ3, filamin is spatiotemporally rearranged to associate with αIIb CT alone on activated αIIbβ3. Consistently, confocal cell imaging indicates that integrin α CT–linked filamin gradually delocalizes from the β CT–linked focal adhesion marker-vinculin likely because of the separation of integrin α/β CTs occurring during integrin activation. High-resolution crystal and nuclear magnetic resonance structure determinations unravel that the activated integrin αIIb CT binds to filamin via a striking α-helix→β-strand transition with a strengthened affinity that is dependent on the integrin-activating membrane environment containing enriched phosphatidylinositol 4,5-bisphosphate. These data suggest a novel integrin αIIb CT–filamin-actin linkage that promotes integrin outside-in signaling. Consistently, disruption of such linkage impairs the activation state of αIIbβ3, phosphorylation of focal adhesion kinase/proto-oncogene tyrosine kinase Src, and cell migration. Together, our findings advance the fundamental understanding of integrin outside-in signaling with broad implications in blood physiology and pathology.

Importance of Nuclear Quantum Effects for NMR Crystallography.

The resolving power of solid-state nuclear magnetic resonance (NMR) crystallography depends heavily on the accuracy of computational predictions of NMR chemical shieldings of candidate structures, which are usually taken to be local minima in the potential energy. To test the limits of this approximation, we systematically study the importance of finite-temperature and quantum nuclear fluctuations for 1H, 13C, and 15N shieldings in polymorphs of three paradigmatic molecular crystals: benzene, glycine, and succinic acid. The effect of quantum fluctuations is comparable to the typical errors of shielding predictions for static nuclei with respect to experiments, and their inclusion improves the agreement with measurements, translating to more reliable assignment of the NMR spectra to the correct candidate structure. The use of integrated machine-learning models, trained on first-principles energies and shieldings, renders rigorous sampling of nuclear fluctuations affordable, setting a new standard for the calculations underlying NMR structure determinations.

NMR Structure Determinations of Small Proteins Using only One Fractionally 20% 13C- and Uniformly 100% 15N-Labeled Sample.

Uniformly 13C- and 15N-labeled samples ensure fast and reliable nuclear magnetic resonance (NMR) assignments of proteins and are commonly used for structure elucidation by NMR. However, the preparation of uniformly labeled samples is a labor-intensive and expensive step. Reducing the portion of 13C-labeled glucose by a factor of five using a fractional 20% 13C- and 100% 15N-labeling scheme could lower the total chemical costs, yet retaining sufficient structural information of uniformly [13C, 15N]-labeled sample as a result of the improved sensitivity of NMR instruments. Moreover, fractional 13C-labeling can facilitate reliable resonance assignments of sidechains because of the biosynthetic pathways of each amino-acid. Preparation of only one [20% 13C, 100% 15N]-labeled sample for small proteins (<15 kDa) could also eliminate redundant sample preparations of 100% 15N-labeled and uniformly 100% [13C, 15N]-labeled samples of proteins. We determined the NMR structures of a small alpha-helical protein, the C domain of IgG-binding protein A from Staphylococcus aureus (SpaC), and a small beta-sheet protein, CBM64 module using [20% 13C, 100% 15N]-labeled sample and compared with the crystal structures and the NMR structures derived from the 100% [13C, 15N]-labeled sample. Our results suggest that one [20% 13C, 100% 15N]-labeled sample of small proteins could be routinely used as an alternative to conventional 100% [13C, 15N]-labeling for backbone resonance assignments, NMR structure determination, 15N-relaxation analysis, and ligand–protein interaction.

Maximizing accuracy of RNA structure in refinement against residual dipolar couplings.

Structural information about ribonucleic acid (RNA) is lagging behind that of proteins, in part due to its high charge and conformational variability. Molecular dynamics (MD) has played an important role in describing RNA structure, complementing information from both nuclear magnetic resonance (NMR), or X-ray crystallography. We examine the impact of the choice of the empirical force field for RNA structure refinement using cross-validation against residual dipolar couplings (RDCs) as structural accuracy reporter. Four force fields, representing both the state-of-the art in RNA simulation and the most popular selections in NMR structure determination, are compared for a prototypical A-RNA helix. RNA structural accuracy is also evaluated as a function of both density and nature of input NMR data including RDCs, anisotropic chemical shifts, and distance restraints. Our results show a complex interplay between the experimental restraints and the force fields indicating two best-performing choices: high-fidelity refinement in explicit solvent, and the conformational database-derived potentials. Accuracy of RNA models closely tracks the density of 1-bond C-H RDCs, with other data types having beneficial, but smaller effects. At lower RDC density, or when refining against NOEs only, the two selected force fields are capable of accurately describing RNA helices with little or no experimental RDC data, making them available for the higher order structure assembly or better quantification of the intramolecular dynamics. Unrestrained simulations of simple RNA motifs with state-of-the art MD force fields appear to capture the flexibility inherent in nucleic acids while also maintaining a good agreement with the experimental observables.

Designing DNA Nanotube Liquid Crystals as a Weak-Alignment Medium for NMR Structure Determination of Membrane Proteins.

Thirty percent of the human proteome is composed of membrane proteins that can perform a wide range of cellular functions and communications. They represent the core of modern medicine as the targets of about 50 % of all prescription pharmaceuticals. However, elucidating the structure of membrane proteins has represented a constant challenge, even in the modern era. To date, only a few hundred high-resolution structural models of membrane proteins are available. This chapter describes the emergence of DNA nanotechnology as a powerful tool for the structural characterization of membrane protein using solution-state nuclear magnetic resonance (NMR) spectroscopy. Here, we detail the large-scale synthesis of detergent-resistant DNA nanotubes that can be assembled into a dilute liquid crystal to be used as a weak-alignment media in solution NMR structure determination of membrane proteins.

NMR in structural genomics to increase structural coverage of the protein universe: Delivered by Prof. Kurt Wüthrich on 7 July 2013 at the 38th FEBS Congress in St. Petersburg, Russia.

For more than a decade, the Joint Center for Structural Genomics (JCSG; www.jcsg.org) worked toward increased three-dimensional structure coverage of the protein universe. This coordinated quest was one of the main goals of the four high-throughput (HT) structure determination centers of the Protein Structure Initiative (PSI; www.nigms.nih.gov/Research/specificareas/PSI). To achieve the goals of the PSI, the JCSG made use of the complementarity of structure determination by X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy to increase and diversify the range of targets entering the HT structure determination pipeline. The overall strategy, for both techniques, was to determine atomic resolution structures for representatives of large protein families, as defined by the Pfam database, which had no structural coverage and could make significant contributions to biological and biomedical research. Furthermore, the experimental structures could be leveraged by homology modeling to further expand the structural coverage of the protein universe and increase biological insights. Here, we describe what could be achieved by this structural genomics approach, using as an illustration the contributions from 20 NMR structure determinations out of a total of 98 JCSG NMR structures, which were selected because they are the first three-dimensional structure representations of the respective Pfam protein families. The information from this small sample is representative for the overall results from crystal and NMR structure determination in the JCSG. There are five new folds, which were classified as domains of unknown functions (DUF), three of the proteins could be functionally annotated based on three-dimensional structure similarity with previously characterized proteins, and 12 proteins showed only limited similarity with previous deposits in the Protein Data Bank (PDB) and were classified as DUFs.

Structural Basis for KCNQ1 Long-QT Syndrome Disease causing Mutations

The human potassium channel KCNQ1 is a polytopic α-helical membrane protein. KCNQ1 is expressed in both epithelial and heart tissue. In the heart, KCNQ1, in association with KCNE1, mediates the Iks current responsible for the repolarization of the cardiac action potential. Mutations that cause a loss-of-function of KCNQ1 result in a congenital condition known as long-QT syndrome (LQTS). Congenital LQTS predisposes an individual to cardiac arrhythmia and can result in sudden death. While current homology models are sufficient to generate testable structure-function hypotheses, low sequence conservation between KCNQ1 and other potassium channel structures, especially in the voltage-sensing domain, highlight the need for an experimentally determined KCNQ1 structure. Our focus is on the KCNQ1 voltage-sensing domain (Q1-VSD) that mediates the voltage response of the ion channel. Isolated Q1-VSDs exist in equilibrium between an open and closed state, likely favoring the open conformation. To facilitate nuclear magnetic resonance (NMR) structural investigation of the Q1-VSD, we employ state-locking mutations that provide a homogeneous reference spectrum. Our goal is to develop a biochemical model for the disease mechanism of specific LQTS mutations. The structural effects of specific LQTS disease-causing mutations are being evaluated in two ways (1) by comparison to the Q1-VSD ‘locked’ open- and closed-state NMR reference spectra and (2) in the context of current KCNQ1 homology models. Preliminary comparison of wild type Q1-VSD to a ‘locked’ closed-state construct by NMR in model membranes indicates a global conformational rearrangement. Ultimately we seek to leverage the closed-state stabilizing mutations to facilitate NMR structure determination of the Q1-VSD in its inactive “down” state.

Nuclear Magnetic Resonance Structure of a Novel Globular Domain in RBM10 Containing OCRE, the Octamer Repeat Sequence Motif

The OCtamer REpeat (OCRE) has been annotated as a 42-residue sequence motif with 12 tyrosine residues in the spliceosome trans-regulatory elements RBM5 and RBM10 (RBM [RNA-binding motif]), which are known to regulate alternative splicing of Fas and Bcl-x pre-mRNA transcripts. Nuclear magnetic resonance structure determination showed that the RBM10 OCRE sequence motif is part of a 55-residue globular domain containing 16 aromatic amino acids, which consists of an anti-parallel arrangement of six β strands, with the first five strands containing complete or incomplete Tyr triplets. This OCRE globular domain is a distinctive component of RBM10 and is more widely conserved in RBM10s across the animal kingdom than the ubiquitous RNA recognition components. It isalso found in the functionally related RBM5. Thus, it appears that the three-dimensional structure of the globular OCRE domain, rather than the 42-residue OCRE sequence motif alone, confers specificity on RBM10 intermolecular interactions in the spliceosome.

RNA dances to center stage.

RNA dances to center stage.

Increased Reliability of Nuclear Magnetic Resonance Protein Structures by Consensus Structure Bundles

Nuclear magnetic resonance (NMR) structures are represented by bundles of conformers calculated from different randomized initial structures using identical experimental input data. The spread among these conformers indicates the precision of the atomic coordinates. However, there is as yet no reliable measure of structural accuracy, i.e., how close NMR conformers are to the "true" structure. Instead, the precision of structure bundles is widely (mis)interpreted as a measure of structural quality. Attempts to increase precision often overestimate accuracy by tight bundles of high precision but much lower accuracy. To overcome this problem, we introduce a protocol for NMR structure determination with the software package CYANA, which produces, like the traditional method, bundles of conformers in agreement with a common set of conformational restraints but with a realistic precision that is, throughout a variety of proteins and NMR data sets, a much better estimate of structural accuracy than the precision of conventional structure bundles.

Structure and Interactions of the CS Domain of Human H/ACA RNP Assembly Protein Shq1

Shq1 is an essential protein involved in the early steps of biogenesis and assembly of H/ACA ribonucleoprotein particles (RNPs). Shq1 binds to dyskerin (Cbf5 in yeast) at an early step of H/ACA RNP assembly and is subsequently displaced by the H/ACA RNA. Shq1 contains an N-terminal CS and a C-terminal Shq1-specific domain (SSD). Dyskerin harbors many mutations associated with dyskeratosis congenita. Structures of yeast Shq1 SSD bound to Cbf5 revealed that only a subset of these mutations is in the SSD binding site, implicating another subset in the putative CS binding site. Here, we present the crystal structure of human Shq1 CS (hCS) and the nuclear magnetic resonance (NMR) and crystal structures of hCS containing a serine substitution for proline 22 that is associated with some prostate cancers. The structure of hCS is similar to yeast Shq1 CS domain (yCS) and consists of two β-sheets that form an immunoglobulin-like β-sandwich fold. The N-terminal affinity tag sequence AHHHHHH associates with a neighboring protein in the crystal lattice to form an extra β-strand. Deletion of this tag was required to get spectra suitable for NMR structure determination, while the tag was required for crystallization. NMR chemical shift perturbation (CSP) experiments with peptides derived from putative CS binding sites on dyskerin and Cbf5 revealed a conserved surface on CS important for Cbf5/dyskerin binding. A HADDOCK (high-ambiguity-driven protein–protein docking) model of a Shq1-Cbf5 complex that defines the position of CS domain in the pre-H/ACA RNP was calculated using the CSP data.

Automatic NOESY assignment in CS-RASREC-Rosetta.

We have developed an approach for simultaneous structure calculation and automatic Nuclear Overhauser Effect (NOE) assignment to solve nuclear magnetic resonance (NMR) structures from unassigned NOESY data. The approach, autoNOE-Rosetta, integrates Resolution Adapted Structural RECombination (RASREC) Rosetta NMR calculations with algorithms for automatic NOE assignment. The method was applied to two proteins in the 15-20 kDa size range for which both, NMR and X-ray data, is available. The autoNOE-Rosetta calculations converge for both proteins and yield accurate structures with an RMSD of 1.9 Å to the X-ray reference structures. The method greatly expands the radius of convergence for automatic NOE assignment, and should be broadly useful for NMR structure determination.

Bayesian Peak Picking for NMR Spectra

Protein structure determination is a very important topic in structural genomics, which helps people to understand varieties of biological functions such as protein-protein interactions, protein–DNA interactions and so on. Nowadays, nuclear magnetic resonance (NMR) has often been used to determine the three-dimensional structures of protein in vivo. This study aims to automate the peak picking step, the most important and tricky step in NMR structure determination. We propose to model the NMR spectrum by a mixture of bivariate Gaussian densities and use the stochastic approximation Monte Carlo algorithm as the computational tool to solve the problem. Under the Bayesian framework, the peak picking problem is casted as a variable selection problem. The proposed method can automatically distinguish true peaks from false ones without preprocessing the data. To the best of our knowledge, this is the first effort in the literature that tackles the peak picking problem for NMR spectrum data using Bayesian method.

Solution NMR refinement of a metal ion bound protein using metal ion inclusive restrained molecular dynamics methods

Correctly calculating the structure of metal coordination sites in a protein during the process of nuclear magnetic resonance (NMR) structure determination and refinement continues to be a challenging task. In this study, we present an accurate and convenient means by which to include metal ions in the NMR structure determination process using molecular dynamics (MD) simulations constrained by NMR-derived data to obtain a realistic and physically viable description of the metal binding site(s). This method provides the framework to accurately portray the metal ions and its binding residues in a pseudo-bond or dummy-cation like approach, and is validated by quantum mechanical/molecular mechanical (QM/MM) MD calculations constrained by NMR-derived data. To illustrate this approach, we refine the zinc coordination complex structure of the zinc sensing transcriptional repressor protein Staphylococcus aureus CzrA, generating over 130 ns of MD and QM/MM MD NMR-data compliant sampling. In addition to refining the first coordination shell structure of the Zn(II) ion, this protocol benefits from being performed in a periodically replicated solvation environment including long-range electrostatics. We determine that unrestrained (not based on NMR data) MD simulations correlated to the NMR data in a time-averaged ensemble. The accurate solution structure ensemble of the metal-bound protein accurately describes the role of conformational sampling in allosteric regulation of DNA binding by zinc and serves to validate our previous unrestrained MD simulations of CzrA. This methodology has potentially broad applicability in the structure determination of metal ion bound proteins, protein folding and metal template protein-design studies.

DNA nanotubes for NMR structure determination of membrane proteins

Finding a way to determine the structures of integral membrane proteins using solution nuclear magnetic resonance (NMR) spectroscopy has proved to be challenging. A residual-dipolar-coupling-based refinement approach can be used to resolve the structure of membrane proteins up to 40 kDa in size, but to do this you need a weak-alignment medium that is detergent-resistant and it has thus far been difficult to obtain such a medium suitable for weak alignment of membrane proteins. We describe here a protocol for robust, large-scale synthesis of detergent-resistant DNA nanotubes that can be assembled into dilute liquid crystals for application as weak-alignment media in solution NMR structure determination of membrane proteins in detergent micelles. The DNA nanotubes are heterodimers of 400-nm-long six-helix bundles, each self-assembled from a M13-based p7308 scaffold strand and >170 short oligonucleotide staple strands. Compatibility with proteins bearing considerable positive charge as well as modulation of molecular alignment, toward collection of linearly independent restraints, can be introduced by reducing the negative charge of DNA nanotubes using counter ions and small DNA-binding molecules. This detergent-resistant liquid-crystal medium offers a number of properties conducive for membrane protein alignment, including high-yield production, thermal stability, buffer compatibility and structural programmability. Production of sufficient nanotubes for four or five NMR experiments can be completed in 1 week by a single individual.

All-Atom Ensemble Modeling to Analyze Small-Angle X-Ray Scattering of Glycosylated Proteins

The flexible and heterogeneous nature of carbohydrate chains often renders glycoproteins refractory to traditional structure determination methods. Small-angle X-ray scattering (SAXS) can be a useful tool for obtaining structural information of these systems. All-atom modeling of glycoproteins with flexible glycan chains was applied to interpret the solution SAXS data for a set of glycoproteins. For simpler systems (single glycan, with a well-defined protein structure), all-atom modeling generates models in excellent agreement with the scattering pattern and reveals the approximate spatial occupancy of the glycan chain in solution. For more complex systems (several glycan chains, or unknown protein substructure), the approach can still provideinsightful models, though the orientations of glycans become poorly determined. Ab initio shape reconstructions appear to capture the global morphology of glycoproteins but in most cases offer littleinformation about glycan spatial occupancy. The all-atom modeling methodology is available as a web server at http://salilab.org/allosmod-foxs.

Two‐dimensional nuclear magnetic resonance structure determination module for introductory biochemistry: synthesis and structural characterization of lyso‐glycerophospholipids

In this laboratory module, introductory biochemistry students are exposed to two-dimensional (1) H-nuclear magnetic resonance of glycerophospholipids (GPLs). Working in groups of three, students enzymatically synthesized and purified a variety of 2-acyl lyso GPLs. The structure of the 2-acyl lyso GPL was verified using (1) H-correlation spectroscopy. Students scored significantly higher on an assessment of NMR knowledge after having participated in this lab module and in comparison to a similar cohort who did not participate. Inaddition, student confidence in their NMR knowledge and abilities increased 62% following the module and correlated with their ability to apply their NMR knowledge. Based on these results, the laboratory module was very effective at providing students with a more extensive understanding of the underlying concepts of NMR as a tool for structural determination.

Requirements on Paramagnetic Relaxation Enhancement Data for Membrane Protein Structure Determination by NMR

Nuclear magnetic resonance (NMR) structure calculations of the α-helical integral membrane proteins DsbB, GlpG, and halorhodopsin show that distance restraints from paramagnetic relaxation enhancement (PRE) can provide sufficient structural information to determine their structure with an accuracy of about 1.5Å in the absence of other long-range conformational restraints. Our systematic study with simulated NMR data shows that about one spin label per transmembrane helix is necessary for obtaining enough PRE distance restraints to exclude wrong topologies, such as pseudo mirror images, if only limited other NMR restraints are available. Consequently, an experimentally realistic amount of PRE data enables α-helical membrane protein structure determinations that would not be feasible with the very limited amount of conventional NOESY data normally available for these systems. These findings are in line with our recent first de novo NMR structure determination of a heptahelical integral membrane protein, proteorhodopsin, that relied extensively on PRE data.