Characterising side chains in large proteins by protonless 13C-detected NMR spectroscopy

A combined NMR and deep neural network approach for enhancing the spectral resolution of aromatic side chains in proteins

Nuclear magnetic resonance (NMR) spectroscopy is an important technique for deriving the dynamics and interactions of macromolecules; however, characterizations of aromatic residues in proteins still pose a challenge. Here, we present a deep neural network (DNN), which transforms NMR spectra recorded on simple uniformly 13C-labeled samples to yield high-quality 1H-13C correlation maps of aromatic side chains. Key to the success of the DNN is the design of NMR experiments that produce data with unique features to aid the DNN produce high-resolution spectra. The methodology was validated experimentally on protein samples ranging from 7 to 40 kDa in size, where it accurately reconstructed multidimensional aromatic 1H-13C correlation maps, to facilitate 1H-13C chemical shift assignments and to quantify kinetics. More generally, we believe that the strategy of designing new NMR experiments in combination with customized DNNs represents a substantial advance that will have a major impact on the study of molecules using NMR in the years to come.

Solution-state methyl NMR spectroscopy of large non-deuterated proteins enabled by deep neural networks

Methyl-TROSY nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for characterising large biomolecules in solution. However, preparing samples for these experiments is demanding and entails deuteration, limiting its use. Here we demonstrate that NMR spectra recorded on protonated, uniformly 13C labelled samples can be processed using deep neural networks to yield spectra that are of similar quality to typical deuterated methyl-TROSY spectra, potentially providing information for proteins that cannot be produced in bacterial systems. We validate the methodology experimentally on three proteins with molecular weights in the range 42-360 kDa. We further demonstrate the applicability of our methodology to 3D NOESY spectra of Escherichia coli Malate Synthase G (81 kDa), where observed NOE cross-peaks are in good agreement with the available structure. The method represents an advance in the field of using deep learning to analyse complex magnetic resonance data and could have an impact on the study of large biomolecules in years to come.

Beyond slow two-state protein conformational exchange using CEST: applications to three-state protein interconversion on the millisecond timescale

Although NMR spectroscopy is routinely used to study the conformational dynamics of biomolecules, robust analyses of the data are challenged in cases where exchange is more complex than two-state, such as when a 'visible' major conformer exchanges with two 'invisible' minor states on the millisecond timescale. It is becoming increasingly clear that chemical exchange saturation transfer (CEST) NMR experiments that were initially developed to study systems undergoing slow interconversion are also sensitive to intermediate-fast timescale biomolecular conformational exchange. Here we investigate the utility of the amide 15N CEST experiment to characterise protein three-state exchange occurring on the millisecond timescale by studying the interconversion between the folded (F) state of the FF domain from human HYPA/FBP11 (WT FF) and two of its folding intermediates I1 and I2. Although 15N CPMG experiments are consistent with the F state interconverting with a single minor state on the millisecond timescale, 15N CEST data clearly establish an exchange process between F and a pair of minor states. A unique three-state exchange model cannot be obtained by analysis of 15N CEST data recorded at a single temperature. However, including the relative sign of the difference in the chemical shifts of the two minor states based on a simple two-state analysis of CEST data recorded at multiple temperatures, results in a robust three-state model in which the F, I1 and I2 states interconvert with each other on the millisecond timescale ( k e x , F I 1 ~ 550 s-1, k e x , F I 2 ~ 1200 s-1, k e x , I 1 I 2 ~ 5000 s-1), with I1 and I2 sparsely populated at ~ 0.15% and ~ 0.35%, respectively, at 15 °C. A computationally demanding grid-search of exchange parameter space is not required to extract the best-fit exchange parameters from the CEST data. The utility of the CEST experiment, thus, extends well beyond studies of conformers in slow exchange on the NMR chemical shift timescale, to include systems with interconversion rates on the order of thousands/second.

Biomolecular NMR in the AI-assisted structural biology era: Old tricks and new opportunities

Over the last 40 years nuclear magnetic resonance (NMR) spectroscopy has established itself as one of the most versatile techniques for the characterization of biomolecules, especially proteins. Given the molecular size limitations of NMR together with recent advances in cryo-electron microscopy and artificial intelligence-assisted protein structure prediction, the bright future of NMR in structural biology has been put into question. In this mini review we argue the contrary. We discuss the unique opportunities solution NMR offers to the protein chemist that distinguish it from all other experimental or computational methods, and how it can benefit from machine learning.

Paramagnetic NMR to study iron sulfur proteins: 13C detected experiments illuminate the vicinity of the metal center

The robustness of NMR coherence transfer in proximity of a paramagnetic center depends on the relaxation properties of the nuclei involved. In the case of Iron-Sulfur Proteins, different pulse schemes or different parameter sets often provide complementary results. Tailored versions of HCACO and CACO experiments significantly increase the number of observed Cα/C' connectivities in highly paramagnetic systems, by recovering many resonances that were lost due to paramagnetic relaxation. Optimized 13C direct detected experiments can significantly extend the available assignments, improving the overall knowledge of these systems. The different relaxation properties of Cα and C' nuclei are exploited in CACO vs COCA experiments and the complementarity of the two experiments is used to obtain structural information. The two [Fe2S2]+ clusters containing NEET protein CISD3 and the one [Fe4S4]2+ cluster containing HiPIP protein PioC have been taken as model systems. We show that tailored experiments contribute to decrease the blind sphere around the cluster, to extend resonance assignment of cluster bound cysteine residues and to retrieve details on the topology of the iron-bound ligand residues.

Biomolecular NMR spectroscopy in the era of artificial intelligence

Biomolecular nuclear magnetic resonance (NMR) spectroscopy and artificial intelligence (AI) have a burgeoning synergy. Deep learning-based structural predictors have forever changed structural biology, yet these tools currently face limitations in accurately characterizing protein dynamics, allostery, and conformational heterogeneity. We begin by highlighting the unique abilities of biomolecular NMR spectroscopy to complement AI-based structural predictions toward addressing these knowledge gaps. We then highlight the direct integration of deep learning approaches into biomolecular NMR methods. AI-based tools can dramatically improve the acquisition and analysis of NMR spectra, enhancing the accuracy and reliability of NMR measurements, thus streamlining experimental processes. Additionally, deep learning enables the development of novel types of NMR experiments that were previously unattainable, expanding the scope and potential of biomolecular NMR spectroscopy. Ultimately, a combination of AI and NMR promises to further revolutionize structural biology on several levels, advance our understanding of complex biomolecular systems, and accelerate drug discovery efforts.

The design of functional proteins using tensorized energy calculations

In protein design, the energy associated with a huge number of sequence-conformer perturbations has to be routinely estimated. Hence, enhancing the throughput and accuracy of these energy calculations can profoundly improve design success rates and enable tackling more complex design problems. In this work, we explore the possibility of tensorizing the energy calculations and apply them in a protein design framework. We use this framework to design enhanced proteins with anti-cancer and radio-tracing functions. Particularly, we designed multispecific binders against ligands of the epidermal growth factor receptor (EGFR), where the tested design could inhibit EGFR activity in vitro and in vivo. We also used this method to design high-affinity Cu2+ binders that were stable in serum and could be readily loaded with copper-64 radionuclide. The resulting molecules show superior functional properties for their respective applications and demonstrate the generalizable potential of the described protein design approach.

Studying micro to millisecond protein dynamics using simple amide 15N CEST experiments supplemented with major-state R2 and visible peak-position constraints

Over the last decade amide 15N CEST experiments have emerged as a popular tool to study protein dynamics that involves exchange between a 'visible' major state and sparsely populated 'invisible' minor states. Although initially introduced to study exchange between states that are in slow exchange with each other (typical exchange rates of, 10 to 400 s-1), they are now used to study interconversion between states on the intermediate to fast exchange timescale while still using low to moderate (5 to 350 Hz) 'saturating' B1 fields. The 15N CEST experiment is very sensitive to exchange as the exchange delay TEX can be quite long (~0.5 s) allowing for a large number of exchange events to occur making it a very powerful tool to detect minor sates populated ([Formula: see text]) to as low as 1%. When systems are in fast exchange and the 15N CEST data has to be described using a model that contains exchange, the exchange parameters are often poorly defined because the [Formula: see text] versus [Formula: see text] and [Formula: see text] versus exchange rate ([Formula: see text]) plots can be quite flat with shallow or no minima and the analysis of such 15N CEST data can lead to wrong estimates of the exchange parameters due to the presence of 'spurious' minima. Here we show that the inclusion of experimentally derived constraints on the intrinsic transverse relaxation rates and the inclusion of visible state peak-positions during the analysis of amide 15N CEST data acquired with moderate B1 values (~50 to ~350 Hz) results in convincing minima in the [Formula: see text] versus [Formula: see text] and the [Formula: see text] versus [Formula: see text] plots even when exchange occurs on the 100 μs timescale. The utility of this strategy is demonstrated on the fast-folding Bacillus stearothermophilus peripheral subunit binding domain that folds with a rate constant ~104 s-1. Here the analysis of 15N CEST data alone results in [Formula: see text] versus [Formula: see text] and [Formula: see text] versus [Formula: see text] plots that contain shallow minima, but the inclusion of visible-state peak positions and restraints on the intrinsic transverse relaxation rates of both states during the analysis of the 15N CEST data results in pronounced minima in the [Formula: see text] versus [Formula: see text] and [Formula: see text] versus [Formula: see text] plots and precise exchange parameters even in the fast exchange regime ([Formula: see text]~5). Using this strategy we find that the folding rate constant of PSBD is invariant (~10,500 s-1) from 33.2 to 42.9 °C while the unfolding rates (~70 to ~500 s-1) and unfolded state populations (~0.7 to ~4.3%) increase with temperature. The results presented here show that protein dynamics occurring on the 10 to 104 s-1 timescale can be studied using amide 15N CEST experiments.

Exploring the Applications of Carbon-Detected NMR in Living and Dead Organisms Using a 13C-Optimized Comprehensive Multiphase NMR Probe

Comprehensive multiphase-nuclear magnetic resonance (CMP-NMR) is a non-invasive approach designed to observe all phases (solutions, gels, and solids) in intact samples using a single NMR probe. Studies of dead and living organisms are important to understand processes ranging from biological growth to environmental stress. Historically, such studies have utilized ¹H-based phase editing for the detection of soluble/swollen components and ¹H-detected 2D NMR for metabolite assignments/screening. However, living organisms require slow spinning rates (∼500 Hz) to increase survivability, but at such low speeds, complications from water sidebands and spectral overlap from the modest chemical shift window (∼0-10 ppm) make ¹H NMR challenging. Here, a novel ¹³C-optimized E-Free magic angle spinning CMP probe is applied to study all phases in ex vivo and in vivo samples. This probe consists of a two-coil design, with an inner single-tuned ¹³C coil providing a 113% increase in ¹³C sensitivity relative to a traditional multichannel single-CMP coil design. For organisms with a large biomass (∼0.1 g) like the Ganges River sprat (ex vivo), ¹³C-detected full spectral editing and ¹³C-detected heteronuclear correlation (HETCOR) can be performed at natural abundance. Unfortunately, for a single living shrimp (∼2 mg), ¹³C enrichment was still required, but ¹³C-detected HETCOR shows superior data relative to heteronuclear single-quantum coherence at low spinning speeds (due to complications from water sidebands in the latter). The probe is equipped with automatic-tuning-matching and is compatible with automated gradient shimming─a key step toward conducting multiphase screening of dead and living organisms under automation in the near future.

13C Direct Detected NMR for Challenging Systems

Thanks to recent improvements in NMR spectrometer hardware and pulse sequence design, modern 13C NMR has become a useful tool for biomolecular applications. The complete assignment of a protein can be accomplished by using 13C detected multinuclear experiments and it can provide unique information relevant for the study of a variety of different biomolecules including paramagnetic proteins and intrinsically disordered proteins. A wide range of NMR observables can be measured, concurring to the structural and dynamic characterization of a protein in isolation, as part of a larger complex, or even inside a living cell. We present the different properties of 13C with respect to 1H, which provide the rationale for the experiments developed and their application, the technical aspects that need to be faced, and the many experimental variants designed to address different cases. Application areas where these experiments successfully complement proton NMR are also described.

Observation of Arginine Side-Chain Motions Coupled to the Global Conformational Exchange Process in Deubiquitinase A

Coupled motions have been demonstrated to be functionally important in a number of enzymes. Noncovalent side-chain interactions play essential roles in coordinating the motions across different structural elements in a protein. However, most of the dynamic studies of proteins are focused on backbone amides or methyl groups in the side chains and little is known about the polar and charged side chains. We have previously characterized the conformational dynamics of deubiquitinase A (DUBA), an isopeptidase, on the microsecond-to-millisecond (μs-ms) time scales with the amide ¹H Carr-Purcell-Meiboom-Gill (CPMG) experiment. We detected a global conformational exchange process on a time scale of approximately 200 μs, which involves most of the structural elements in DUBA, including the active site and the substrate binding interface. Here, we extend our previous study on backbone amides to the arginine side-chain N^ε-H^ε groups using a modified ¹H CPMG pulse sequence that can efficiently detect both backbone amide and arginine side-chain N^ε-H^ε signals in a single experiment. We found that the side chains of three arginines display motions on the same time scale as the backbone amides. Mutations of two of the three arginines to alanines result in a decrease in enzyme activity. One of these two arginines is located in a loop involved in substrate binding. This loop is not visible in the backbone amide-detected experiments due to excess line broadening induced by motions on the μs-ms time scales. These results clearly demonstrate that the motions of some arginine side chains are coupled to the global conformational exchange process and provide an additional probe for motions in a functionally important loop that did not yield visible backbone amide signals, suggesting the value of side-chain experiments on DUBA. The modified ¹H CPMG pulse sequence allows the simultaneous characterization of backbone and arginine side-chain dynamics without any increase in data acquisition time and can be applied to the dynamic studies of any protein that displays measurable amide ¹H relaxation dispersion.

Large Chaperone Complexes Through the Lens of Nuclear Magnetic Resonance Spectroscopy

Molecular chaperones are the guardians of the proteome inside the cell. Chaperones recognize and bind unfolded or misfolded substrates, thereby preventing further aggregation; promoting correct protein folding; and, in some instances, even disaggregating already formed aggregates. Chaperones perform their function by means of an array of weak protein-protein interactions that take place over a wide range of timescales and are therefore invisible to structural techniques dependent upon the availability of highly homogeneous samples. Nuclear magnetic resonance (NMR) spectroscopy, however, is ideally suited to study dynamic, rapidly interconverting conformational states and protein-protein interactions in solution, even if these involve a high-molecular-weight component. In this review, we give a brief overview of the principles used by chaperones to bind their client proteins and describe NMR methods that have emerged as valuable tools to probe chaperone-substrate and chaperone-chaperone interactions. We then focus on a few systems for which the application of these methods has greatly increased our understanding of the mechanisms underlying chaperone functions. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

nightshift: A Python program for plotting simulated NMR spectra from assigned chemical shifts from the Biological Magnetic Resonance Data Bank

Nuclear magnetic resonance (NMR) provides site specific information on local environments through chemical shifts. NMR is widely used in the study of proteins, ranging from determination of three-dimensional (3D) structures to characterizing dynamics and binding of small molecules and other proteins or ligands. Assigned chemical shift data for the atoms within proteins is a treasure trove of information that can facilitate a broad range of biochemical and biophysical studies. The Biological Magnetic Resonance Data Bank (BMRB) is a publicly accessible database that contains a large number of assigned chemical shifts; however, translating this wealth of knowledge into a practical application is not straightforward. Herein we present nightshift: a Python command line utility and library for plotting simulated two-dimensional (2D) and 3D NMR spectra from assigned chemical shifts in the BMRB. This tool allows users to simulate routinely collected amide and methyl fingerprint spectra, backbone triple-resonance assignment spectra, and user-defined custom correlations, including ones that do not necessarily correspond to published experiments. This tool enables experienced NMR spectroscopists, those learning the craft, and interested scientists seeking to utilize NMR the ability to preview or examine a wide range of spectra for proteins whose assignments are deposited in the BMRB, irrespective of whether those experiments have been executed or reported. The tool applies equally to folded and intrinsically disordered proteins, limited only by the existence of a BMRB deposition. The features of nightshift are described along with applications that illustrate the ease with which complicated correlation spectra and binding events can be simulated.

Virtual Homonuclear Decoupling in Direct Detection Nuclear Magnetic Resonance Experiments Using Deep Neural Networks

Nuclear magnetic resonance (NMR) experiments are frequently complicated by the presence of homonuclear scalar couplings. For the growing body of biomolecular 13C-detected NMR methods, one-bond 13C-13C couplings significantly reduce sensitivity and resolution. The solution to this problem has typically been to perform virtual decoupling by recording multiple spectra and taking linear combinations. Here, we propose an alternative method of virtual decoupling using deep neural networks, which only requires a single spectrum and gives a significant boost in resolution while reducing the minimum effective phase cycles of the experiments by at least a factor of 2. We successfully apply this methodology to virtually decouple in-phase CON (13CO-15N) protein NMR spectra, 13C-13C correlation spectra of protein side chains, and 13Cα-detected protein 13Cα-13CO spectra where two large homonuclear couplings are present. The deep neural network approach effectively decouples spectra with a high degree of flexibility, including in cases where existing methods fail, and facilitates the use of simpler pulse sequences.

Observation of Sub-Microsecond Protein Methyl-Side Chain Dynamics by Nanoparticle-Assisted NMR Spin Relaxation

Amino-acid side-chain properties in proteins are key determinants of protein function. NMR spin relaxation of side chains is an important source of information about local protein dynamics and flexibility. However, traditional solution NMR relaxation methods are most sensitive to sub-nanosecond dynamics lacking information on slower ns-μs time-scale motions. Nanoparticle-assisted NMR spin relaxation (NASR) of methyl-side chains is introduced here as a window into these ns-μs dynamics. NASR utilizes the transient and nonspecific interactions between folded proteins and slowly tumbling spherical nanoparticles (NPs), whereby the increase of the relaxation rates reflects motions on time scales from ps all the way to the overall tumbling correlation time of the NPs ranging from hundreds of ns to μs. The observed motional amplitude of each methyl group can then be expressed by a model-free NASR S² order parameter. The method is demonstrated for ²H-relaxation of CH₂D methyl moieties and cross-correlated relaxation of CH₃ groups for proteins Im7 and ubiquitin in the presence of anionic silica-nanoparticles. Both types of relaxation experiments, dominated by either quadrupolar or dipolar interactions, yield highly consistent results. Im7 shows additional dynamics on the intermediate time scales taking place in a functionally important loop, whereas ubiquitin visits the majority of its conformational substates on the sub-ns time scale. These experimental observations are in good agreement with 4-10 μs all-atom molecular dynamics trajectories. NASR probes side-chain dynamics on a much wider range of motional time scales than previously possible, thereby providing new insights into the interplay between protein structure, dynamics, and molecular interactions that govern protein function.

Methodological advancements for characterising protein side chains by NMR spectroscopy

The surface of proteins is covered by side chains of polar amino acids that are imperative for modulating protein functionality through the formation of noncovalent intermolecular interactions. However, despite their tremendous importance, the unique structures of protein side chains require tailored approaches for investigation by nuclear magnetic resonance spectroscopy and so have traditionally been understudied compared with the protein backbone. Here, we review substantial recent methodological advancements within nuclear magnetic resonance spectroscopy to address this issue. Specifically, we consider advancements that provide new insight into methyl-bearing side chains, show the potential of using non-natural amino acids and reveal the actions of charged side chains. Combined, the new methods promise unprecedented characterisations of side chains that will further elucidate protein function.

15N CPMG Relaxation Dispersion for the Investigation of Protein Conformational Dynamics on the µs-ms Timescale

Protein conformational dynamics play fundamental roles in regulation of enzymatic catalysis, ligand binding, allostery, and signaling, which are important biological processes. Understanding how the balance between structure and dynamics governs biological function is a new frontier in modern structural biology and has ignited several technical and methodological developments. Among these, CPMG relaxation dispersion solution NMR methods provide unique, atomic-resolution information on the structure, kinetics, and thermodynamics of protein conformational equilibria occurring on the µs-ms timescale. Here, the study presents detailed protocols for acquisition and analysis of a ¹⁵N relaxation dispersion experiment. As an example, the pipeline for the analysis of the µs-ms dynamics in the C-terminal domain of bacteria Enzyme I is shown.

NMR spectroscopy captures the essential role of dynamics in regulating biomolecular function

Biomolecules are in constant motion. To understand how they function, and why malfunctions can cause disease, it is necessary to describe their three-dimensional structures in terms of dynamic conformational ensembles. Here, we demonstrate how nuclear magnetic resonance (NMR) spectroscopy provides an essential, dynamic view of structural biology that captures biomolecular motions at atomic resolution. We focus on examples that emphasize the diversity of biomolecules and biochemical applications that are amenable to NMR, such as elucidating functional dynamics in large molecular machines, characterizing transient conformations implicated in the onset of disease, and obtaining atomic-level descriptions of intrinsically disordered regions that make weak interactions involved in liquid-liquid phase separation. Finally, we discuss the pivotal role that NMR has played in driving forward our understanding of the biomolecular dynamics-function paradigm.

Racemic phosphorothioate as a tool for NMR investigations of protein-DNA complexes

A major driving force for protein-nucleic acid association is electrostatic interactions via ion pairs of the positively charged basic side chains and negatively charged phosphates. For a better understanding of how proteins scan DNA and recognize particular signatures, it is important to gain atomic-level insight into the behavior of basic side chains at the protein-DNA interfaces. NMR spectroscopy is a powerful tool for investigating the structural, dynamic, and kinetic aspects of protein-DNA interactions. However, resonance assignment of basic side-chain cationic moieties at the molecular interfaces remains to be a major challenge. Here, we propose a fast, robust, and inexpensive approach that greatly facilitates resonance assignment of interfacial moieties and also allows for kinetic measurements of protein translocation between two DNA duplexes. This approach utilizes site-specific incorporation of racemic phosphorothioate at the position of a phosphate that interacts with a protein side chain. This modification retains the electric charge of phosphate and therefore is mild, but causes significant chemical shift perturbations for the proximal protein side chains, which facilitates resonance assignment. Due to the racemic nature of the modification, two different chemical shifts are observed for the species with different diastereomers R_P and S_P of the incorporated phosphorothioate group. Kinetic information on the exchange of the protein molecule between R_P and S_P DNA duplexes can be obtained by ¹⁵N_z exchange spectroscopy. We demonstrate the applications of this approach to the Antennapedia homeodomain-DNA complex and the CREB1 basic leucine-zipper (bZIP)-DNA complex.

A CEST NMR experiment to obtain glycine 1Hα chemical shifts in 'invisible' minor states of proteins

Chemical exchange saturation transfer (CEST) experiments are routinely used to study protein conformational exchange between a 'visible' major state and 'invisible' minor states because they can detect minor states with lifetimes varying from ~ 3 to ~ 100 ms populated to just ~ 0.5%. Consequently several ¹H, ¹⁵N and ¹³C CEST experiments have been developed to study exchange and obtain minor state chemical shifts at almost all backbone and sidechain sites in proteins. Conspicuously missing from this extensive set of CEST experiments is a ¹H CEST experiment to study exchange at glycine (Gly) ¹H^α sites as the existing ¹H CEST experiments that have been designed to study dynamics in amide ¹H-¹⁵N spin systems and methyl ¹³CH₃ groups with three equivalent protons while suppressing ¹H-¹H NOE induced dips are not suitable for studying exchange in methylene ¹³CH₂ groups with inequivalent protons. Here a Gly ¹H^α CEST experiment to obtain the minor state Gly ¹H^α chemical shifts is presented. The utility of this experiment is demonstrated on the L99A cavity mutant of T4 Lysozyme (T4L L99A) that undergoes conformational exchange between two compact conformers. The CEST derived minor state Gly ¹H^α chemical shifts of T4L L99A are in agreement with those obtained previously using CPMG techniques. The experimental strategy presented here can also be used to obtain methylene proton minor state chemical shifts from protein sidechain and nucleic acid backbone sites.

Multiquantum Chemical Exchange Saturation Transfer NMR to Quantify Symmetrical Exchange: Application to Rotational Dynamics of the Guanidinium Group in Arginine Side Chains

Chemical exchange saturation transfer (CEST) NMR experiments have emerged as a powerful tool for characterizing dynamics in proteins. We show here that the CEST approach can be extended to systems with symmetrical exchange, where the NMR signals of all exchanging species are severely broadened. To achieve this, multiquantum CEST (MQ-CEST) is introduced, where the CEST pulse is applied to a longitudinal multispin order density element and the CEST profiles are encoded onto nonbroadened nuclei. The MQ-CEST approach is demonstrated on the restricted rotation of guanidinium groups in arginine residues within proteins. These groups and their dynamics are essential for many enzymes and for noncovalent interactions through the formation of hydrogen bonds, salt-bridges, and π-stacking interactions, and their rate of rotation is highly indicative of the extent of interactions formed. The MQ-CEST method is successfully applied to guanidinium groups in the 19 kDa L99A mutant of T4 lysozyme.

Intra-residue methyl-methyl correlations for valine and leucine residues in large proteins from a 3D-HMBC-HMQC experiment

Methyl-TROSY based NMR experiments have over the last two decades become one of the most important means to characterise dynamics and functional mechanisms of large proteins and macromolecular machines in solution. The chemical shift assignment of methyl groups in large proteins is, however, still not trivial and it is typically performed using backbone-dependent experiments in a 'divide and conquer' approach, mutations, structure-based assignments or a combination of these. Structure-based assignment of methyl groups is an emerging strategy, which reduces the time and cost required as well as providing a method that is independent of a backbone assignment. One crucial step in available structure-based assignment protocols is linking the two prochiral methyl groups of leucine and valine residues. This has previously been achieved by recording NOESY spectra with short mixing times or by comparing NOESY spectra. Herein, we present a method based on through-bond scalar coupling transfers, a 3D-HMBC-HMQC experiment, to link the intra-residue methyl groups of leucine and valine. It is shown that the HMBC-HMQC method has several advantages over solely using NOESY spectra since a unique intra-residue cross-peak is observed. Moreover, overlap in the methyl-TROSY HMQC spectrum can easily be identified with the HMBC-HMQC experiment, thereby removing possible ambiguities in the assignment.

The Ambivalent Role of Proline Residues in an Intrinsically Disordered Protein: From Disorder Promoters to Compaction Facilitators

Intrinsically disordered proteins (IDPs) carry out many biological functions. They lack a stable three-dimensional structure, but rather adopt many different conformations in dynamic equilibrium. The interplay between local dynamics and global rearrangements is key for their function. In IDPs, proline residues are significantly enriched. Given their unique physicochemical and structural properties, a more detailed understanding of their potential role in stabilizing partially folded states in IDPs is highly desirable. Nuclear magnetic resonance (NMR) spectroscopy, and in particular ¹³C-detected NMR, is especially suitable to address these questions. We applied a ¹³C-detected strategy to study Osteopontin, a largely disordered IDP with a central compact region. By using the exquisite sensitivity and spectral resolution of these novel techniques, we gained unprecedented insight into cis-Pro populations, their local structural dynamics, and their role in mediating long-range contacts. Our findings clearly call for a reassessment of the structural and functional role of proline residues in IDPs. The emerging picture shows that proline residues have ambivalent structural roles. They are not simply disorder promoters but rather can, depending on the primary sequence context, act as nucleation sites for structural compaction in IDPs. These unexpected features provide a versatile mechanistic toolbox to enrich the conformational ensembles of IDPs with specific features for adapting to changing molecular and cellular environments.