Accelerated NMR spectroscopy by using compressed sensing

RNA Binding Properties of SOX Family Members

SOX proteins are a family of transcription factors (TFs) that play critical functions in sex determination, neurogenesis, and chondrocyte differentiation, as well as cardiac, vascular, and lymphatic development. There are 20 SOX family members in humans, each sharing a 79-residue L-shaped high mobility group (HMG)-box domain that is responsible for DNA binding. SOX2 was recently shown to interact with long non-coding RNA and large-intergenic non-coding RNA to regulate embryonic stem cell and neuronal differentiation. The RNA binding region was shown to reside within the HMG-box domain; however, the structural details of this binding remain unclear. Here, we show that all SOX family members, except group H, interact with RNA. Our mutational experiments demonstrate that the disordered C-terminal region of the HMG-box domain plays an important role in RNA binding. Further, by determining a high-resolution structure of the HMG-box domain of the group H family member SOX30, we show that despite differences in RNA binding ability, SOX30 shares a very similar secondary structure with other SOX protein HMG-box domains. Together, our study provides insight into the interaction of SOX TFs with RNA.

An extended interaction site determines binding between AP180 and AP2 in clathrin mediated endocytosis

The early phases of clathrin mediated endocytosis are organized through a highly complex interaction network mediated by clathrin associated sorting proteins (CLASPs) that comprise long intrinsically disordered regions (IDRs). AP180 is a CLASP exclusively expressed in neurons and comprises a long IDR of around 600 residues, whose function remains partially elusive. Using NMR spectroscopy, we discovered an extended and strong interaction site within AP180 with the major adaptor protein AP2, and describe its binding dynamics at atomic resolution. We find that the 70 residue-long site determines the overall interaction between AP180 and AP2 in a dynamic equilibrium between its bound and unbound states, while weaker binding sites contribute to the overall affinity at much higher concentrations of AP2. Our data suggest that this particular interaction site might play a central role in recruitment of adaptors to the clathrin coated pit, whereas more transient and promiscuous interactions allow reshaping of the interaction network until cargo uptake inside a coated vesicle.

Non-uniform sampling to enhance the performance of compact NMR for characterizing new psychoactive substances

Efficient and robust analytical methods are needed to improve the identification and subsequent regulation of new psychoactive substances (NPS). NMR spectroscopy is a unique method able to determine the structure of small molecules such as NPS even in mixtures. However, high-field NMR analysis is associated with expensive purchase and maintenance costs. For more than a decade, compact NMR spectrometers have changed this paradigm. It was recently shown that a dedicated analytical workflow combining compact NMR and databases could identify the molecular structure of NPS, in spite of the lower spectral dispersion and sensitivity of compact spectrometers. This approach relies on 1H-13C HSQC to both recognize NPS and elucidate the structure of unknown substances. Still, its performance is limited by the need to compromise between resolution and experiment time. Here, we show that this strategy can be significantly improved by implementing non-uniform sampling (NUS) to improve spectral resolution in the 13C dimension of HSQC at no cost in terms of experiment time. Gains in the range of 3 to 4 in resolution are achieved for pure NPS and for a mixture. Finally, 2D HSQC with NUS was applied to improve the identification of NPS with the assistance of databases. The resulting method appears as a useful tool for the characterization of NPS in mixtures, which is essential for forensic laboratories.

Functional selection in SH3-mediated activation of the PI3 kinase

The phosphoinositide-3 kinase (PI3K), a heterodimeric enzyme, plays a pivotal role in cellular metabolism and survival. Its deregulation is associated with major human diseases, particularly cancer. The p85 regulatory subunit of PI3K binds to the catalytic p110 subunit via its C-terminal domains, stabilising it in an inhibited state. Certain Src homology 3 (SH3) domains can activate p110 by binding to the proline-rich (PR) 1 motif located at the N-terminus of p85. However, the mechanism by which this N-terminal interaction activates the C-terminally bound p110 remains elusive. Moreover, the intrinsically poor ligand selectivity of SH3 domains raises the question of how they can control PI3K. Combining structural, biophysical, and functional methods, we demonstrate that the answers to both these unknown issues are linked: PI3K-activating SH3 domains engage in additional "tertiary" interactions with the C-terminal domains of p85, thereby relieving their inhibition of p110. SH3 domains lacking these tertiary interactions may still bind to p85 but cannot activate PI3K. Thus, p85 uses a functional selection mechanism that precludes nonspecific activation rather than nonspecific binding. This separation of binding and activation may provide a general mechanism for how biological activities can be controlled by promiscuous protein-protein interaction domains.

LDHB contributes to the regulation of lactate levels and basal insulin secretion in human pancreatic β cells

Using 13C6 glucose labeling coupled to gas chromatography-mass spectrometry and 2D 1H-13C heteronuclear single quantum coherence NMR spectroscopy, we have obtained a comparative high-resolution map of glucose fate underpinning β cell function. In both mouse and human islets, the contribution of glucose to the tricarboxylic acid (TCA) cycle is similar. Pyruvate fueling of the TCA cycle is primarily mediated by the activity of pyruvate dehydrogenase, with lower flux through pyruvate carboxylase. While the conversion of pyruvate to lactate by lactate dehydrogenase (LDH) can be detected in islets of both species, lactate accumulation is 6-fold higher in human islets. Human islets express LDH, with low-moderate LDHA expression and β cell-specific LDHB expression. LDHB inhibition amplifies LDHA-dependent lactate generation in mouse and human β cells and increases basal insulin release. Lastly, cis-instrument Mendelian randomization shows that low LDHB expression levels correlate with elevated fasting insulin in humans. Thus, LDHB limits lactate generation in β cells to maintain appropriate insulin release.

Efficient Access to Elusive 1D 13C NMR Spectra through Highly Resolved 1H, 13C-Long-Range Correlation Spectroscopy

A method for obtaining 1D 13C NMR spectra from natural products or metabolites using proton detection is described. The approach delivers singlets for every 13C signal without conducting any broadband 1H decoupling (CPD) and is based on calculating 13C projections from constant-time HMBC and conventional HSQC experiments, recorded at high digital resolution and processed to pure phases. Paramount to the proposed method is the implication of nonuniform sampling and echo processing. The echo processing produces phase-sensitive 2D CT-HMBC spectra with narrow 13C signal line shapes. Two simple HMBC pulse sequences are utilized with the suppression of homo- and heteronuclear couplings. Due to the removal of the 1H multiplet structure in F1 (no tilt at higher digital resolution), 13C singlets arise. An overall increase in 13C signal-to-noise (SINO) for all types of carbon multiplicities is observed, making the proposed technique superior compared to direct 13C excitation. For otherwise difficult-to-measure quaternary carbon atoms, a SINO enhancement of up to 6 and 12 depending on F1 resolution (3 and 6 Hz/point) is reported. Echo/anti-Echo signal detection cleans up the spectrum. Nonuniform sampling (NUS) lays the groundwork to significantly reduce the total acquisition time. Final 1D 13C projections are obtained by combining the 13C projection from CT HMBC and conventional HSQC. This orthogonal concept of combining the 13C projections from different spectra inherently minimizes the risk of missing 13C cross-peaks by inappropriate setting of long-range nJHC coupling delays and the shortcoming of T2 relaxations. The advantages and some limitations of the concept are discussed.

A set of cross-correlated relaxation experiments to probe the correlation time of two different and complementary spin pairs

Intrinsically disordered proteins (IDPs) defy the conventional structure-function paradigm by lacking a well-defined tertiary structure and exhibiting inherent flexibility. This flexibility leads to distinctive spin relaxation modes, reflecting isolated and specific motions within individual peptide planes. In this work, we propose a new pulse sequence to measure the longitudinal 13C' CSA-13C'-13Cα DD CCR rate [Formula: see text] and present a novel 3D version of the transverse [Formula: see text] CCR rate, adopting the symmetrical reconversion approach. We combined these rates with the analogous ΓxyN/NH and ΓzN/NH CCR rates to derive residue-specific correlation times for both spin-pairs within the same peptide plane. The presented approach offers a straightforward and intuitive way to compare the correlation times of two different and complementary spin vectors, anticipated to be a valuable aid to determine IDPs backbone dihedral angles distributions. We performed the proposed experiments on two systems: a folded protein ubiquitin and Coturnix japonica osteopontin, a prototypical IDP. Comparative analyses of the results show that the correlation times of different residues vary more for IDPs than globular proteins, indicating that the dynamics of IDPs is largely heterogeneous and dominated by local fluctuations.

Cargo selective vesicle tethering: The structural basis for binding of specific cargo proteins by the Golgi tether component TBC1D23

The Golgi-localized golgins golgin-97 and golgin-245 capture transport vesicles arriving from endosomes via the protein TBC1D23. The amino-terminal domain of TBC1D23 binds to the golgins, and the carboxyl-terminal domain of TBC1D23 captures the vesicles, but how it recognizes specific vesicles was unclear. A search for binding partners of the carboxyl-terminal domain unexpectedly revealed direct binding to carboxypeptidase D and syntaxin-16, known cargo proteins of the captured vesicles. Binding is via a threonine-leucine-tyrosine (TLY) sequence present in both proteins next to an acidic cluster. A crystal structure reveals how this acidic TLY motif binds to TBC1D23. An acidic TLY motif is also present in the tails of other endosome-to-Golgi cargo, and these also bind TBC1D23. Structure-guided mutations in the carboxyl-terminal domain that disrupt motif binding in vitro also block vesicle capture in vivo. Thus, TBC1D23 attached to golgin-97 and golgin-245 captures vesicles by a previously undescribed mechanism: the recognition of a motif shared by cargo proteins carried by the vesicle.

Poly-γ-glutamylation of biomolecules

Poly-γ-glutamate tails are a distinctive feature of archaeal, bacterial, and eukaryotic cofactors, including the folates and F420. Despite decades of research, key mechanistic questions remain as to how enzymes successively add glutamates to poly-γ-glutamate chains while maintaining cofactor specificity. Here, we show how poly-γ-glutamylation of folate and F420 by folylpolyglutamate synthases and γ-glutamyl ligases, non-homologous enzymes, occurs via processive addition of L-glutamate onto growing γ-glutamyl chain termini. We further reveal structural snapshots of the archaeal γ-glutamyl ligase (CofE) in action, crucially including a bulged-chain product that shows how the cofactor is retained while successive glutamates are added to the chain terminus. This bulging substrate model of processive poly-γ-glutamylation by terminal extension is arguably ubiquitous in such biopolymerisation reactions, including addition to folates, and demonstrates convergent evolution in diverse species from archaea to humans.

Accelerated Pure Shift NMR Spectroscopy with Deep Learning

Pure shift nuclear magnetic resonance (NMR) spectroscopy presents a promising solution to provide sufficient spectral resolution and has been increasingly applied in various branches of chemistry, but the optimal resolution is generally accompanied by long experimental times. We present a proof of concept of deep learning for fast, high-quality, and reliable pure shift NMR reconstruction. The deep learning (DL) protocol allows one to eliminate undersampling artifacts, distinguish peaks with close chemical shifts, and reconstruct high-resolution pure shift NMR spectroscopy along with accelerated acquisition. More meaningfully, the lightweight neural network delivers satisfactory reconstruction performance on personal computers by several hundred simulated data learning, which somewhat lifts the prohibiting demand for a large volume of real training samples and advanced computing hardware generally required in DL projects. Additionally, an M-to-S strategy applicable to common DL cases is further exploited to boost the network generalization capability. As a result, this study takes a meaningful step toward deep learning protocols for broad chemical applications.

Disease-specific tau filaments assemble via polymorphic intermediates

Intermediate species in the assembly of amyloid filaments are believed to play a central role in neurodegenerative diseases and may constitute important targets for therapeutic intervention1,2. However, structural information about intermediate species has been scarce and the molecular mechanisms by which amyloids assemble remain largely unknown. Here we use time-resolved cryogenic electron microscopy to study the in vitro assembly of recombinant truncated tau (amino acid residues 297-391) into paired helical filaments of Alzheimer's disease or into filaments of chronic traumatic encephalopathy3. We report the formation of a shared first intermediate amyloid filament, with an ordered core comprising residues 302-316. Nuclear magnetic resonance indicates that the same residues adopt rigid, β-strand-like conformations in monomeric tau. At later time points, the first intermediate amyloid disappears and we observe many different intermediate amyloid filaments, with structures that depend on the reaction conditions. At the end of both assembly reactions, most intermediate amyloids disappear and filaments with the same ordered cores as those from human brains remain. Our results provide structural insights into the processes of primary and secondary nucleation of amyloid assembly, with implications for the design of new therapies.

Single-Scan Ultraselective NMR Experiments with Preserved Sensitivity

Selective NMR experiments provide rapid access to important structural information, and are essential to tackle the analysis of large molecules and complex mixtures. Single-scan ultraselective experiments are particularly useful, as they can rapidly select signals that overlap with other signals. Here, we describe a novel type of single-scan ultraselective NMR experiments that is robust against the effects of translational molecular diffusion, and thus make it possible to improve significantly the sensitivity of the experiment. This will largely broaden the applicability of this powerful class of experiments.

Combined NMR and molecular dynamics conformational filter identifies unambiguously dynamic ensembles of Dengue protease NS2B/NS3pro

The dengue protease NS2B/NS3pro has been reported to adopt either an 'open' or a 'closed' conformation. We have developed a conformational filter that combines NMR with MD simulations to identify conformational ensembles that dominate in solution. Experimental values derived from relaxation parameters for the backbone and methyl side chains were compared with the corresponding back-calculated relaxation parameters of different conformational ensembles obtained from free MD simulations. Our results demonstrate a high prevalence for the 'closed' conformational ensemble while the 'open' conformation is absent, indicating that the latter conformation is most probably due to crystal contacts. Conversely, conformational ensembles in which the positioning of the co-factor NS2B results in a 'partially' open conformation, previously described in both MD simulations and X-ray studies, were identified by our conformational filter. Altogether, we believe that our approach allows for unambiguous identification of true conformational ensembles, an essential step for reliable drug discovery.

Exploring Sulfur Sites in Proteins via Triple-Resonance 1H-Detected 77Se NMR

NMR spectroscopy has been applied to virtually all sites within proteins and biomolecules; however, the observation of sulfur sites remains very challenging. Recent studies have examined 77Se as a replacement for sulfur and applied 77Se NMR in both the solution and solid states. As a spin-1/2 nuclide, 77Se is attractive as a probe of sulfur sites, and it has a very large chemical shift range (due to a large chemical shift anisotropy), which makes it potentially very sensitive to structural and/or binding interactions as well as dynamics. Despite being a spin-1/2 nuclide, there have been rather limited studies of 77Se, and the ability to use 1H-indirect detection has been sparse. Some examples exist, but in the absence of a directly bonded, nonexchangeable 1H, these have been largely limited to smaller molecules. We develop and illustrate approaches using double-labeling of 13C and 77Se in proteins that enable more sensitive triple-resonance schemes via multistep coherence transfers and 1H-detection. These methods require specialized hardware and decoupling schemes, which we developed and will be discussed.

Targeted imaging of uPAR expression in vivo with cyclic AE105 variants

A comprehensive literature reports on the correlation between elevated levels of urokinase-type plasminogen activator receptor (uPAR) and the severity of diseases with chronic inflammation including solid cancers. Molecular imaging is widely used as a non-invasive method to locate disease dissemination via full body scans and to stratify patients for targeted treatment. To date, the only imaging probe targeting uPAR that has reached clinical phase-II testing relies on a high-affinity 9-mer peptide (AE105), and several studies by positron emission tomography (PET) scanning or near-infra red (NIR) fluorescence imaging have validated its utility and specificity in vivo. While our previous studies focused on applying various reporter groups, the current study aims to improve uPAR-targeting properties of AE105. We successfully stabilized the small uPAR-targeting core of AE105 by constraining its conformational landscape by disulfide-mediated cyclization. Importantly, this modification mitigated the penalty on uPAR-affinity typically observed after conjugation to macrocyclic chelators. Cyclization did not impair tumor targeting efficiency of AE105 in vivo as assessed by PET imaging and a trend towards increased tracer uptake was observed. In future studies, we predict that this knowledge will aid development of new fluorescent AE105 derivatives with a view to optical imaging of uPAR to assist precision guided cancer surgery.

Expanding the Limits of Structural Characterization of Marine Dissolved Organic Matter Using Nonuniform Sampling Frequency-Reversed Edited HSQC NMR

The multiplicity-edited heteronuclear single quantum correlation (ME-HSQC) NMR method is widely used for the structural characterization of marine dissolved organic matter (DOM), which is a complex molecular mixture comprising millions of individual compounds. However, the standard ME-HSQC suffers from significant signal cancellation and subsequent loss of crucial structural information due to the overlap between CH3/CH (positive) and CH2 (negative) cross-peaks in overcrowded regions. This study introduces nonuniform sampling in frequency-reversed ME-HSQC (NUS FR-ME-HSQC), highlighting its remarkable potential for the comprehensive structural characterization of marine DOM. By reversing the frequency of CH2 cross-peaks into an empty region, the FR-ME-HSQC method effectively simplifies the spectra and eliminates signal cancellation. We demonstrate that nonuniform sampling enables the acquisition of comparable spectra in half the time or significantly enhances the sensitivity in time-equivalent spectra. Comparative analysis also identifies vulnerable CH2 cross-peaks in the standard ME-HSQC that coincide with CH3 and CH cross-peaks, resulting in the loss of critical structural details. In contrast, the NUS FR-ME-HSQC retains these missing correlations, enabling in-depth characterization of marine DOM. These findings highlight the potential of NUS FR-ME-HSQC as an advanced NMR technique that effectively addresses challenges such as signal overcrowding and prolonged experimental times, enabling the thorough investigation of complex mixtures with implications in several fields, including chemistry, metabolomics, and environmental sciences. The advantages of NUS FR-ME-HSQC are experimentally demonstrated on two solid-phase-extracted DOM (SPE-DOM) samples from the surface and deep ocean. With this new technology, differences in the composition of DOM from various aquatic environments can be assigned to individual molecules.

A Sparse Model-Inspired Deep Thresholding Network for Exponential Signal Reconstruction-Application in Fast Biological Spectroscopy

The nonuniform sampling (NUS) is a powerful approach to enable fast acquisition but requires sophisticated reconstruction algorithms. Faithful reconstruction from partially sampled exponentials is highly expected in general signal processing and many applications. Deep learning (DL) has shown astonishing potential in this field, but many existing problems, such as lack of robustness and explainability, greatly limit its applications. In this work, by combining the merits of the sparse model-based optimization method and data-driven DL, we propose a DL architecture for spectra reconstruction from undersampled data, called MoDern. It follows the iterative reconstruction in solving a sparse model to build the neural network, and we elaborately design a learnable soft-thresholding to adaptively eliminate the spectrum artifacts introduced by undersampling. Extensive results on both synthetic and biological data show that MoDern enables more robust, high-fidelity, and ultrafast reconstruction than the state-of-the-art methods. Remarkably, MoDern has a small number of network parameters and is trained on solely synthetic data while generalizing well to biological data in various scenarios. Furthermore, we extend it to an open-access and easy-to-use cloud computing platform (XCloud-MoDern), contributing a promising strategy for further development of biological applications.

The RavA-ViaA chaperone complex modulates bacterial persistence through its association with the fumarate reductase enzyme

Regulatory ATPase variant A (RavA) is a MoxR AAA+ protein that functions together with a partner protein termed von Willebrand factor type A interacting with AAA+ ATPase (ViaA). RavA-ViaA are functionally associated with anaerobic respiration in Escherichia coli through interactions with the fumarate reductase (Frd) electron transport complex. Through this association, RavA and ViaA modulate the activity of the Frd complex and, hence, are proposed to have chaperone-like activity. However, the functional role of RavA-ViaA in the cell is not yet well established. We had demonstrated that RavA-ViaA can sensitize E. coli cells to sublethal concentrations of the aminoglycoside class of antibiotics. Since Frd has been associated with bacterial persistence against antibiotics, the relationship of RavA-ViaA and Frd was explored within this context. Experiments performed here reveal a function of RavA-ViaA in bacterial persistence upon treatment with antibiotics through the association of the chaperone complex with Frd. As part of this work, the NMR structure of the N-terminal domain of ViaA was solved. The structure reveals a novel alpha helical fold, which we name the VAN fold, that has not been observed before. We show that this domain is required for the function of the chaperone complex. We propose that modulating the levels of RavA-ViaA could enhance the susceptibility of Gram-negative bacteria to antibiotics.

Mitochondrial Metabolism in the Spotlight: Maintaining Balanced RNAP III Activity Ensures Cellular Homeostasis

RNA polymerase III (RNAP III) holoenzyme activity and the processing of its products have been linked to several metabolic dysfunctions in lower and higher eukaryotes. Alterations in the activity of RNAP III-driven synthesis of non-coding RNA cause extensive changes in glucose metabolism. Increased RNAP III activity in the S. cerevisiae maf1Δ strain is lethal when grown on a non-fermentable carbon source. This lethal phenotype is suppressed by reducing tRNA synthesis. Neither the cause of the lack of growth nor the underlying molecular mechanism have been deciphered, and this area has been awaiting scientific explanation for a decade. Our previous proteomics data suggested mitochondrial dysfunction in the strain. Using model mutant strains maf1Δ (with increased tRNA abundance) and rpc128-1007 (with reduced tRNA abundance), we collected data showing major changes in the TCA cycle metabolism of the mutants that explain the phenotypic observations. Based on 13C flux data and analysis of TCA enzyme activities, the present study identifies the flux constraints in the mitochondrial metabolic network. The lack of growth is associated with a decrease in TCA cycle activity and downregulation of the flux towards glutamate, aspartate and phosphoenolpyruvate (PEP), the metabolic intermediate feeding the gluconeogenic pathway. rpc128-1007, the strain that is unable to increase tRNA synthesis due to a mutation in the C128 subunit, has increased TCA cycle activity under non-fermentable conditions. To summarize, cells with non-optimal activity of RNAP III undergo substantial adaptation to a new metabolic state, which makes them vulnerable under specific growth conditions. Our results strongly suggest that balanced, non-coding RNA synthesis that is coupled to glucose signaling is a fundamental requirement to sustain a cell's intracellular homeostasis and flexibility under changing growth conditions. The presented results provide insight into the possible role of RNAP III in the mitochondrial metabolism of other cell types.

Exponential Signal Reconstruction With Deep Hankel Matrix Factorization

Exponential function is a basic form of temporal signals, and how to fast acquire this signal is one of the fundamental problems and frontiers in signal processing. To achieve this goal, partial data may be acquired but result in severe artifacts in its spectrum, which is the Fourier transform of exponentials. Thus, reliable spectrum reconstruction is highly expected in the fast data acquisition in many applications, such as chemistry, biology, and medical imaging. In this work, we propose a deep learning method whose neural network structure is designed by imitating the iterative process in the model-based state-of-the-art exponentials' reconstruction method with the low-rank Hankel matrix factorization. With the experiments on synthetic data and realistic biological magnetic resonance signals, we demonstrate that the new method yields much lower reconstruction errors and preserves the low-intensity signals much better than compared methods.

Non-uniform sampling of similar NMR spectra and its application to studies of the interaction between alpha-synuclein and liposomes

The accelerated acquisition of multidimensional NMR spectra using sparse non-uniform sampling (NUS) has been widely adopted in recent years. The key concept in NUS is that a major part of the data is omitted during measurement, and then reconstructed using, for example, compressed sensing (CS) methods. CS requires spectra to be compressible, that is, they should contain relatively few "significant" points. The more compressible the spectrum, the fewer experimental NUS points needed in order for it to be accurately reconstructed. In this paper we show that the CS processing of similar spectra can be enhanced by reconstructing only the differences between them. Accurate reconstruction can be obtained at lower sampling levels as the difference is sparser than the spectrum itself. In many situations this method is superior to "conventional" compressed sensing. We exemplify the concept of "difference CS" with one such case-the study of alpha-synuclein binding to liposomes and its dependence on temperature. To obtain information on temperature-dependent transitions between different states, we need to acquire several dozen spectra at various temperatures, with and without the presence of liposomes. Our detailed investigation reveals that changes in the binding modes of the alpha-synuclein ensemble are not only temperature-dependent but also show non-linear behavior in their transitions. Our proposed CS processing approach dramatically reduces the number of NUS points required and thus significantly shortens the experimental time.

The opening dynamics of the lateral gate regulates the activity of rhomboid proteases

Rhomboid proteases hydrolyze substrate helices within the lipid bilayer to release soluble domains from the membrane. Here, we investigate the mechanism of activity regulation for this unique but wide-spread protein family. In the model rhomboid GlpG, a lateral gate formed by transmembrane helices TM2 and TM5 was previously proposed to allow access of the hydrophobic substrate to the shielded hydrophilic active site. In our study, we modified the gate region and either immobilized the gate by introducing a maleimide-maleimide (M2M) crosslink or weakened the TM2/TM5 interaction network through mutations. We used solid-state nuclear magnetic resonance (NMR), molecular dynamics (MD) simulations, and molecular docking to investigate the resulting effects on structure and dynamics on the atomic level. We find that variants with increased dynamics at TM5 also exhibit enhanced activity, whereas introduction of a crosslink close to the active site strongly reduces activity. Our study therefore establishes a strong link between the opening dynamics of the lateral gate in rhomboid proteases and their enzymatic activity.

Multipurpose Broadband NMR Inversion Sequences

Solution-state 2D correlation experiments increase signal-to-noise, provide improved resolution, and inform about molecular connectivity. NMR experiments are compromised when the nuclei have broad chemical shift ranges that exceed the bandwidth of the experiment. Spectra acquired under these conditions are unphasable and artifact-prone, and peaks may disappear from the spectrum altogether. Existing remedies provide usable spectra only in specific experimental contexts. Here, we introduce a general broadband strategy that leads to a library of high performing NMR experiments. We achieve arbitrary and independent evolution of NMR interactions by only changing delays in our pulse block, letting the block replace inversion elements in any NMR experiment. The experiments improve the experimental bandwidth for both nuclei by an order of magnitude over conventional sequences, covering chemical shift ranges of most molecules, even at ultrahigh field. This library enables robust spectroscopy of molecules such as perfluorinated oils (¹⁹F{¹³C}) and fluorophosphorous compounds in battery electrolytes (¹⁹F{³¹P}).

Stabilization of pre-existing neurotensin receptor conformational states by β-arrestin-1 and the biased allosteric modulator ML314

The neurotensin receptor 1 (NTS1) is a G protein-coupled receptor (GPCR) with promise as a drug target for the treatment of pain, schizophrenia, obesity, addiction, and various cancers. A detailed picture of the NTS1 structural landscape has been established by X-ray crystallography and cryo-EM and yet, the molecular determinants for why a receptor couples to G protein versus arrestin transducers remain poorly defined. We used 13CεH3-methionine NMR spectroscopy to show that binding of phosphatidylinositol-4,5-bisphosphate (PIP2) to the receptor's intracellular surface allosterically tunes the timescale of motions at the orthosteric pocket and conserved activation motifs - without dramatically altering the structural ensemble. β-arrestin-1 further remodels the receptor ensemble by reducing conformational exchange kinetics for a subset of resonances, whereas G protein coupling has little to no effect on exchange rates. A β-arrestin biased allosteric modulator transforms the NTS1:G protein complex into a concatenation of substates, without triggering transducer dissociation, suggesting that it may function by stabilizing signaling incompetent G protein conformations such as the non-canonical state. Together, our work demonstrates the importance of kinetic information to a complete picture of the GPCR activation landscape.

Recombinant Production, NMR Solution Structure, and Membrane Interaction of the Phα1β Toxin, a TRPA1 Modulator from the Brazilian Armed Spider Phoneutria nigriventer

Phα1β (PnTx3-6) is a neurotoxin from the spider Phoneutria nigriventer venom, originally identified as an antagonist of two ion channels involved in nociception: N-type voltage-gated calcium channel (Ca_V2.2) and TRPA1. In animal models, Phα1β administration reduces both acute and chronic pain. Here, we report the efficient bacterial expression system for the recombinant production of Phα1β and its ¹⁵N-labeled analogue. Spatial structure and dynamics of Phα1β were determined via NMR spectroscopy. The N-terminal domain (Ala1-Ala40) contains the inhibitor cystine knot (ICK or knottin) motif, which is common to spider neurotoxins. The C-terminal α-helix (Asn41-Cys52) stapled to ICK by two disulfides exhibits the µs-ms time-scale fluctuations. The Phα1β structure with the disulfide bond patterns Cys1-5, Cys2-7, Cys3-12, Cys4-10, Cys6-11, Cys8-9 is the first spider knottin with six disulfide bridges in one ICK domain, and is a good reference to other toxins from the ctenitoxin family. Phα1β has a large hydrophobic region on its surface and demonstrates a moderate affinity for partially anionic lipid vesicles at low salt conditions. Surprisingly, 10 µM Phα1β significantly increases the amplitude of diclofenac-evoked currents and does not affect the allyl isothiocyanate (AITC)-evoked currents through the rat TRPA1 channel expressed in Xenopus oocytes. Targeting several unrelated ion channels, membrane binding, and the modulation of TRPA1 channel activity allow for considering Phα1β as a gating modifier toxin, probably interacting with S1-S4 gating domains from a membrane-bound state.

An Optimized Two-Dimensional Quantitative Nuclear Magnetic Resonance Strategy for the Rapid Quantitation of Diester-Type C19-Diterpenoid Alkaloids from Aconitum carmichaelii

With the development of nuclear magnetic resonance (NMR) spectrometers and probes, two-dimensional quantitative nuclear magnetic resonance (2D qNMR) technology with a high signal resolution and great application potential has become increasingly accessible for the quantitation of complex mixtures. However, the requirement that the relaxation recovery time be equal to at least five times T₁ (longitudinal relaxation time) makes it difficult for 2D qNMR to simultaneously achieve high quantitative accuracy and high data acquisition efficiency. By comprehensively using relaxation optimization and nonuniform sampling, we successfully established an optimized 2D qNMR strategy for HSQC experiments at the half-hour level and then accurately quantified the diester-type C₁₉-diterpenoid alkaloids in Aconitum carmichaelii. The optimized strategy had the advantages of high efficiency, high accuracy, good reproducibility, and low cost and thus could serve as a reference to optimize 2D qNMR experiments for quantitative analysis of natural products, metabolites, and other complex mixtures.

Automated analysis for multiplet identification from ultra-high resolution 2D- 1H, 13C-HSQC NMR spectra

Background: Metabolism is essential for cell survival and proliferation. A deep understanding of the metabolic network and its regulatory processes is often vital to understand and overcome disease. Stable isotope tracing of metabolism using nuclear magnetic resonance (NMR) and mass spectrometry (MS) is a powerful tool to derive mechanistic information of metabolic network activity. However, to retrieve meaningful information, automated tools are urgently needed to analyse these complex spectra and eliminate the bias introduced by manual analysis. Here, we present a data-driven algorithm to automatically annotate and analyse NMR signal multiplets in 2D- ¹H, ¹³C-HSQC NMR spectra arising from ¹³C - ¹³C scalar couplings. The algorithm minimises the need for user input to guide the analysis of 2D- ¹H, ¹³C-HSQC NMR spectra by performing automated peak picking and multiplet analysis. This enables non-NMR specialists to use this technology. The algorithm has been integrated into the existing MetaboLab software package. Methods: To evaluate the algorithm performance two criteria are tested: is the peak correctly annotated and secondly how confident is the algorithm with its analysis. For the latter a coefficient of determination is introduced. Three datasets were used for testing. The first was to test reproducibility with three biological replicates, the second tested the robustness of the algorithm for different amounts of scaling of the apparent J-coupling constants and the third focused on different sampling amounts. Results: The algorithm annotated overall >90% of NMR signals correctly with average coefficient of determination ρ of 94.06 ± 5.08%, 95.47 ± 7.20% and 80.47 ± 20.98% respectively. Conclusions: Our results indicate that the proposed algorithm accurately identifies and analyses NMR signal multiplets in ultra-high resolution 2D- ¹H, ¹³C-HSQC NMR spectra. It is robust to signal splitting enhancement and up to 25% of non-uniform sampling.

Tyrosine kinases compete for growth hormone receptor binding and regulate receptor mobility and degradation

Growth hormone (GH) acts via JAK2 and LYN to regulate growth, metabolism, and neural function. However, the relationship between these tyrosine kinases remains enigmatic. Through an interdisciplinary approach combining cell biology, structural biology, computation, and single-particle tracking on live cells, we find overlapping LYN and JAK2 Box1-Box2-binding regions in GH receptor (GHR). Our data implicate direct competition between JAK2 and LYN for GHR binding and imply divergent signaling profiles. We show that GHR exhibits distinct mobility states within the cell membrane and that activation of LYN by GH mediates GHR immobilization, thereby initiating its nanoclustering in the membrane. Importantly, we observe that LYN mediates cytokine receptor degradation, thereby controlling receptor turnover and activity, and this applies to related cytokine receptors. Our study offers insight into the molecular interactions of LYN with GHR and highlights important functions for LYN in regulating GHR nanoclustering, signaling, and degradation, traits broadly relevant to many cytokine receptors.

Structural analysis of ING3 protein and histone H3 binding

Proteins belonging to the ING family regulate the transcriptional state of chromatin by recruiting remodeling complexes to sites with histone H3 trimethylated at Lysine 4 (H3K4me3). This modification is recognized by the Plant HomeoDomain (PHD) present at the C-terminal region of the five ING proteins. ING3 facilitates acetylation of histones H2A and H4 by the NuA4-Tip60 MYST histone acetyl transferase complex, and it has been proposed to be an oncoprotein. The crystal structure of the N-terminal domain of ING3 shows that it forms homodimers with an antiparallel coiled-coil fold. The crystal structure of the PHD is similar to those of its four homologs. These structures explain the possible deleterious effects of ING3 mutations detected in tumors. The PHD binds histone H3K4me3 with low-micromolar, and binds the non-methylated histone with a 54-fold reduced affinity. Our structure explains the impact of site directed mutagenesis experiments on histone recognition. These structural features could not be confirmed for the full-length protein as solubility was insufficient for structural studies, but the structure of its folded domains suggest a conserved structural organization for the ING proteins as homodimers and bivalent readers of the histone H3K4me3 mark.

Resolution enhancement of NMR by decoupling with the low-rank Hankel model

Nuclear magnetic resonance (NMR) spectroscopy has become a formidable tool for biochemistry and medicine. Although J-coupling carries essential structural information it may also limit the spectral resolution. Homonuclear decoupling remains a challenging problem. In this work, we introduce a new approach that uses a specific coupling value as prior knowledge, and the Hankel property of the exponential NMR signal to achieve broadband heteronuclear decoupling using the low-rank method. Our results on synthetic and realistic HMQC spectra demonstrate that the proposed method not only effectively enhances resolution by decoupling, but also maintains sensitivity and suppresses spectral artefacts. The approach can be combined with non-uniform sampling, which means that the resolution can be further improved without any extra acquisition time.

Structural characterization of human tryptophan hydroxylase 2 reveals that L-Phe is superior to L-Trp as the regulatory domain ligand

Tryptophan hydroxylase 2 (TPH2) catalyzes the rate-limiting step in serotonin biosynthesis in the brain. Consequently, regulation of TPH2 is relevant for serotonin-related diseases, yet the regulatory mechanism of TPH2 is poorly understood and structural and dynamical insights are missing. We use NMR spectroscopy to determine the structure of a 47 N-terminally truncated variant of the regulatory domain (RD) dimer of human TPH2 in complex with L-Phe, and show that L-Phe is the superior RD ligand compared with the natural substrate, L-Trp. Using cryo-EM, we obtain a low-resolution structure of a similarly truncated variant of the complete tetrameric enzyme with dimerized RDs. The cryo-EM two-dimensional (2D) class averages additionally indicate that the RDs are dynamic in the tetramer and likely exist in a monomer-dimer equilibrium. Our results provide structural information on the RD as an isolated domain and in the TPH2 tetramer, which will facilitate future elucidation of TPH2's regulatory mechanism.

ANXA11 biomolecular condensates facilitate protein-lipid phase coupling on lysosomal membranes

Phase transitions of cellular proteins and lipids play a key role in governing the organisation and coordination of intracellular biology. The frequent juxtaposition of proteinaceous biomolecular condensates to cellular membranes raises the intriguing prospect that phase transitions in proteins and lipids could be co-regulated. Here we investigate this possibility in the ribonucleoprotein (RNP) granule-ANXA11-lysosome ensemble, where ANXA11 tethers RNP granule condensates to lysosomal membranes to enable their co-trafficking. We show that changes to the protein phase state within this system, driven by the low complexity ANXA11 N-terminus, induce a coupled phase state change in the lipids of the underlying membrane. We identify the ANXA11 interacting proteins ALG2 and CALC as potent regulators of ANXA11-based phase coupling and demonstrate their influence on the nanomechanical properties of the ANXA11-lysosome ensemble and its capacity to engage RNP granules. The phenomenon of protein-lipid phase coupling we observe within this system offers an important template to understand the numerous other examples across the cell whereby biomolecular condensates closely juxtapose cell membranes.

GRAPHICAL ABSTRACT

Granger causality for compressively sensed sparse signals

Compressed sensing is a scheme that allows for sparse signals to be acquired, transmitted, and stored using far fewer measurements than done by conventional means employing the Nyquist sampling theorem. Since many naturally occurring signals are sparse (in some domain), compressed sensing has rapidly seen popularity in a number of applied physics and engineering applications, particularly in designing signal and image acquisition strategies, e.g., magnetic resonance imaging, quantum state tomography, scanning tunneling microscopy, and analog to digital conversion technologies. Contemporaneously, causal inference has become an important tool for the analysis and understanding of processes and their interactions in many disciplines of science, especially those dealing with complex systems. Direct causal analysis for compressively sensed data is required to avoid the task of reconstructing the compressed data. Also, for some sparse signals, such as for sparse temporal data, it may be difficult to discover causal relations directly using available data-driven or model-free causality estimation techniques. In this work, we provide a mathematical proof that structured compressed sensing matrices, specifically circulant and Toeplitz, preserve causal relationships in the compressed signal domain, as measured by Granger causality (GC). We then verify this theorem on a number of bivariate and multivariate coupled sparse signal simulations which are compressed using these matrices. We also demonstrate a real world application of network causal connectivity estimation from sparse neural spike train recordings from rat prefrontal cortex. In addition to demonstrating the effectiveness of structured matrices for GC estimation from sparse signals, we also show a computational time advantage of the proposed strategy for causal inference from compressed signals of both sparse and regular autoregressive processes as compared to standard GC estimation from original signals.

Conformational Dynamics of Phytoglobin BvPgb1.2 from Beta vulgaris ssp. vulgaris

Plant hemoglobins, often referred to as phytoglobins, play important roles in abiotic stress tolerance. Several essential small physiological metabolites can be bound to these heme proteins. In addition, phytoglobins can catalyze a range of different oxidative reactions in vivo. These proteins are often oligomeric, but the degree and relevance of subunit interactions are largely unknown. In this study, we delineate which residues are involved in dimer formation of a sugar beet phytoglobin type 1.2 (BvPgb1.2) using NMR relaxation experiments. E. coli cells harboring a phytoglobin expression vector were cultivated in isotope-labeled (²H, ¹³C and ¹⁵N) M9 medium. The triple-labeled protein was purified to homogeneity using two chromatographic steps. Two forms of BvPgb1.2 were examined, the oxy-form and the more stable cyanide-form. Using three-dimensional triple-resonance NMR experiments, sequence-specific assignments for CN-bound BvPgb1.2 were achieved for 137 backbone amide cross-peaks in the ¹H-¹⁵N TROSY spectrum, which amounts to 83% of the total number of 165 expected cross-peaks. A large proportion of the non-assigned residues are located in α-helixes G and H, which are proposed to be involved in protein dimerization. Such knowledge around dimer formation will be instrumental for developing a better understanding of phytoglobins' roles in planta.

Structure and IgE Cross-Reactivity among Cashew, Pistachio, Walnut, and Peanut Vicilin-Buried Peptides

Peanut and tree-nut allergies are frequently comorbid for reasons not completely understood. Vicilin-buried peptides (VBPs) are an emerging family of food allergens whose conserved structural fold could mediate peanut/tree-nut co-allergy. Peptide microarrays were used to identify immunoglobulin E (IgE) epitopes from the N-terminus of the vicilin allergens Ara h 1, Ana o 1, Jug r 2, and Pis v 3 using serum from three patient diagnosis groups: monoallergic to either peanuts or cashew/pistachio, or dual allergic. IgE binding peptides were highly prevalent in the VBP domains AH1.1, AO1.1, JR2.1, and PV3.1, but not in AO1.2, JR2.2, JR2.3, and PV3.2 nor the unstructured regions. The IgE profiles did not correlate with diagnosis group. The structure of the VBPs from cashew and pistachio was solved using solution-NMR. Comparisons of structural features suggest that the VBP scaffold from peanuts and tree-nuts can support cross-reactivity. This may help understand comorbidity and cross-reactivity despite a distant evolutionary origin.

Ligands selectively tune the local and global motions of neurotensin receptor 1 (NTS1)

Nuclear magnetic resonance (NMR) studies have revealed that fast methyl sidechain dynamics can report on entropically-driven allostery. Yet, NMR applications have been largely limited to the super-microsecond motional regimes of G protein-coupled receptors (GPCRs). We use ¹³C^ε-methionine chemical shift-based global order parameters to test if ligands affect the fast dynamics of a thermostabilized GPCR, neurotensin receptor 1 (NTS₁). We establish that the NTS₁ solution ensemble includes substates with lifetimes on several, discrete timescales. The longest-lived states reflect those captured in agonist- and inverse agonist-bound crystal structures, separated by large energy barriers. We observe that the rapid fluctuations of individual methionine residues, superimposed on these long-lived states, respond collectively with the degree of fast, global dynamics correlating with ligand pharmacology. This approach lends confidence to interpreting spectra in terms of local structure and methyl dihedral angle geometry. The results suggest a role for sub-microsecond dynamics and conformational entropy in GPCR ligand discrimination.

Primary Structure of Glycans by NMR Spectroscopy

Glycans, carbohydrate molecules in the realm of biology, are present as biomedically important glycoconjugates and a characteristic aspect is that their structures in many instances are branched. In determining the primary structure of a glycan, the sugar components including the absolute configuration and ring form, anomeric configuration, linkage(s), sequence, and substituents should be elucidated. Solution state NMR spectroscopy offers a unique opportunity to resolve all these aspects at atomic resolution. During the last two decades, advancement of both NMR experiments and spectrometer hardware have made it possible to unravel carbohydrate structure more efficiently. These developments applicable to glycans include, inter alia, NMR experiments that reduce spectral overlap, use selective excitations, record tilted projections of multidimensional spectra, acquire spectra by multiple receivers, utilize polarization by fast-pulsing techniques, concatenate pulse-sequence modules to acquire several spectra in a single measurement, acquire pure shift correlated spectra devoid of scalar couplings, employ stable isotope labeling to efficiently obtain homo- and/or heteronuclear correlations, as well as those that rely on dipolar cross-correlated interactions for sequential information. Refined computer programs for NMR spin simulation and chemical shift prediction aid the structural elucidation of glycans, which are notorious for their limited spectral dispersion. Hardware developments include cryogenically cold probes and dynamic nuclear polarization techniques, both resulting in enhanced sensitivity as well as ultrahigh field NMR spectrometers with a ¹H NMR resonance frequency higher than 1 GHz, thus improving resolution of resonances. Taken together, the developments have made and will in the future make it possible to elucidate carbohydrate structure in great detail, thereby forming the basis for understanding of how glycans interact with other molecules.

NMR spectrum reconstruction as a pattern recognition problem

A new deep neural network based on the WaveNet architecture (WNN) is presented, which is designed to grasp specific patterns in the NMR spectra. When trained at a fixed non-uniform sampling (NUS) schedule, the WNN benefits from pattern recognition of the corresponding point spread function (PSF) pattern produced by each spectral peak resulting in the highest quality and robust reconstruction of the NUS spectra as demonstrated in simulations and exemplified in this work on 2D ¹H-¹⁵N correlation spectra of three representative globular proteins with different sizes: Ubiquitin (8.6 kDa), Azurin (14 kDa), and Malt1 (44 kDa). The pattern recognition by WNN is also demonstrated for successful virtual homo-decoupling in a 2D methyl ¹H-¹³C - HMQC spectrum of MALT1. We demonstrate using WNN that prior knowledge about the NUS schedule, which so far was not been fully exploited, can be used for designing new powerful NMR processing techniques that surpass the existing algorithmic methods.

NMR methods for the analysis of mixtures

NMR spectroscopy is a powerful approach for the analysis of mixtures. Its usefulness arises in large part from the vast landscape of methods, and corresponding pulse sequences, that have been and are being designed to tackle the specific properties of mixtures of small molecules. This feature article describes a selection of methods that aim to address the complexity, the low concentrations, and the changing nature that mixtures can display. These notably include pure-shift and diffusion NMR methods, hyperpolarisation methods, and fast 2D NMR methods such as ultrafast 2D NMR and non-uniform sampling. Examples or applications are also described, in fields such as reaction monitoring and metabolomics, to illustrate the relevance and limitations of different methods.

Kövér K. Ultrahigh-Resolution Homo- and Heterodecoupled 1H and TOCSY NMR Experiments

The original homonuclear decoupled (pure shift) experiments provide ultrahigh-resolution ¹H spectra of compounds containing NMR-active heteronuclei of low natural isotopic abundance (e.g., ¹³C or ¹⁵N). In contrast, molecules containing highly abundant heteronuclei (like ³¹P or ¹⁹F) give doublets or a multiple of doublets in their homonuclear decoupled spectra, depending on the number of heteronuclear coupling partners and the magnitude of the respective coupling constants. In these cases, the complex and frequently overlapping signals may hamper the unambiguous assignment of resonances. Here, we present new heteronuclear decoupled (HD) PSYCHE ¹H and TOCSY experiments, which result in simplified spectra with significantly increased resolution, allowing the reliable assessment of individual resonances. The utility of the experiments has been demonstrated on a challenging stereoisomeric mixture of a platinum-phosphine complex, where ultrahigh resolution of the obtained HD PSYCHE spectra made the structure elucidation of the chiral products feasible. HD PSYCHE methods can be potentially applied to other important ³¹P- or ¹⁹F-containing compounds in medicinal chemistry and metabolomics.

Identifying molecular functional groups of organic compounds by deep learning of NMR data

We preprocess the raw nuclear magnetic resonance (NMR) spectrum and extract key features by using two different methodologies, called equidistant sampling and peak sampling for subsequent substructure pattern recognition. We also provide a strategy to address the imbalance issue frequently encountered in statistical modeling of NMR data set and establish two conventional support vector machine (SVM) and K-nearest neighbor (KNN) models to assess the capability of two feature selections, respectively. Our results in this study show that the models using the selected features of peak sampling outperform those using equidistant sampling. Then we build the recurrent neural network (RNN) model trained by data collected from peak sampling. Furthermore, we illustrate the easier optimization of hyperparameters and the better generalization ability of the RNN deep learning model by detailed comparison with traditional machine learning SVM and KNN models.

Automated analysis for multiplet identification from ultra-high resolution 2D-1H,13C-HSQC NMR spectra

Background: Metabolism is essential for cell survival and proliferation. A deep understanding of the metabolic network and its regulatory processes is often vital to understand and overcome disease. Stable isotope tracing of metabolism using nuclear magnetic resonance (NMR) and mass spectrometry (MS) is a powerful tool to derive mechanistic information of metabolic network activity. However, to retrieve meaningful information, automated tools are urgently needed to analyse these complex spectra and eliminate the bias introduced by manual analysis. Here, we present a data-driven algorithm to automatically annotate and analyse NMR signal multiplets in 2D-1H,13C-HSQC NMR spectra arising from 13C -13C scalar couplings. The algorithm minimises the need for user input to guide the analysis of 2D-1H,13C-HSQC NMR spectra by performing automated peak picking and multiplet analysis. This enables non-NMR specialists to use this technology. The algorithm has been integrated into the existing MetaboLab software package. Methods: To evaluate the algorithm performance two criteria are tested: is the peak correctly annotated and secondly how confident is the algorithm with its analysis. For the latter a coefficient of determination is introduced. Three datasets were used for testing. The first was to test reproducibility with three biological replicates, the second tested the robustness of the algorithm for different amounts of scaling of the apparent J-coupling constants and the third focused on different sampling amounts. Results: The algorithm annotated overall >90% of NMR signals correctly with average coefficient of determination ρ of 94.06 ± 5.08%, 95.47 ± 7.20% and 80.47 ± 20.98% respectively. Conclusions: Our results indicate that the proposed algorithm accurately identifies and analyses NMR signal multiplets in ultra-high resolution 2D-1H,13C-HSQC NMR spectra. It is robust to signal splitting enhancement and up to 25% of non-uniform sampling.

Linear discriminant analysis reveals hidden patterns in NMR chemical shifts of intrinsically disordered proteins

NMR spectroscopy is key in the study of intrinsically disordered proteins (IDPs). Yet, even the first step in such an analysis-the assignment of observed resonances to particular nuclei-is often problematic due to low peak dispersion in the spectra of IDPs. We show that the assignment process can be aided by finding "hidden" chemical shift patterns specific to the amino acid residue types. We find such patterns in the training data from the Biological Magnetic Resonance Bank using linear discriminant analysis, and then use them to classify spin systems in an α-synuclein sample prepared by us. We describe two situations in which the procedure can greatly facilitate the analysis of NMR spectra. The first involves the mapping of spin systems chains onto the protein sequence, which is part of the assignment procedure-a prerequisite for any NMR-based protein analysis. In the second, the method supports assignment transfer between similar samples. We conducted experiments to demonstrate these cases, and both times the majority of spin systems could be unambiguously assigned to the correct residue types.

De novo design of immunoglobulin-like domains

Antibodies, and antibody derivatives such as nanobodies, contain immunoglobulin-like (Ig) β-sandwich scaffolds which anchor the hypervariable antigen-binding loops and constitute the largest growing class of drugs. Current engineering strategies for this class of compounds rely on naturally existing Ig frameworks, which can be hard to modify and have limitations in manufacturability, designability and range of action. Here, we develop design rules for the central feature of the Ig fold architecture—the non-local cross-β structure connecting the two β-sheets—and use these to design highly stable Ig domains de novo, confirm their structures through X-ray crystallography, and show they can correctly scaffold functional loops. Our approach opens the door to the design of antibody-like scaffolds with tailored structures and superior biophysical properties.

The immunoglobulin domain framework of antibodies has been a long standing design challenge. Here, the authors describe design rules for tailoring these domains and show they can be accurately designed, de novo, with high stability and the ability to scaffold functional loops.

Backbone and side chain resonance assignment of the intrinsically disordered human DBNDD1 protein

The dysbindin domain-containing protein 1 (DBNDD1) is a conserved protein among higher eukaryotes whose structure and function are poorly investigated so far. Here, we present the backbone and side chain nuclear magnetic resonance assignments for the human DBNDD1 protein. Our chemical-shift based secondary structure analysis reveals the human DBNDD1 as an intrinsically disordered protein.

Assignment of IVL-Methyl side chain of the ligand-free monomeric human MALT1 paracaspase-IgL3 domain in solution

Mucosa-associated lymphoid tissue protein 1 (MALT1) plays a key role in adaptive immune responses by modulating specific intracellular signalling pathways that control the development and proliferation of both T and B cells. Dysfunction of these pathways is coupled to the progress of highly aggressive lymphoma as well as to potential development of an array of different immune disorders. In contrast to other signalling mediators, MALT1 is not only activated through the formation of the CBM complex together with the proteins CARMA1 and Bcl10, but also by acting as a protease that cleaves multiple substrates to promote lymphocyte proliferation and survival via the NF-κB signalling pathway. Herein, we present the partial ¹H, ¹³C Ile/Val/Leu-Methyl resonance assignment of the monomeric apo form of the paracaspase-IgL₃ domain of human MALT1. Our results provide a solid ground for future elucidation of both the three-dimensional structure and the dynamics of MALT1, key for adequate development of inhibitors, and a thorough molecular understanding of its function(s).

Interdomain Dynamics via Paramagnetic NMR on the Highly Flexible Complex Calmodulin/Munc13-1

Paramagnetic NMR constraints are very useful to study protein interdomain motion, but their interpretation is not always straightforward. On the example of the particularly flexible complex Calmodulin/Munc13-1, we present a new approach to characterize this motion with pseudocontact shifts and residual dipolar couplings. Using molecular mechanics, we sampled the conformational space of the complex and used a genetic algorithm to find ensembles that are in agreement with the data. We used the Bayesian information criterion to determine the ideal ensemble size. This way, we were able to make an accurate, unambiguous, reproducible model of the interdomain motion of Calmodulin/Munc13-1 without prior knowledge about the domain orientation from crystallography.

Small molecule SJ572946 activates BAK to initiate apoptosis

Poration of the outer mitochondrial membrane by the effector BCL-2 proteins BAK and BAX initiates apoptosis. BH3-only initiators BID and BIM trigger conformational changes in BAK and BAX transforming them from globular dormant proteins to oligomers of the apoptotic pores. Small molecules that can directly activate effectors are being sought for applications in cancer treatment. Here, we describe the small molecule SJ572946, discovered in a fragment-based screen that binds to the activation groove of BAK and selectively triggers BAK activation over that of BAX in liposome and mitochondrial permeabilization assays. SJ572946 independently kills BAK-expressing BCL2allKO HCT116 cells revealing on target cellular activity. In combination with apoptotic inducers and BH3 mimetics, SJ572946 kills experimental cancer cell lines. SJ572946 also cooperates with the endogenous BAK activator BID in activating a misfolded BAK mutant substantially impaired in activation. SJ572946 is a proof-of-concept tool for probing BAK-mediated apoptosis in preclinical cancer research.

Membrane permeabilization is mediated by distinct epitopes in mouse and human orthologs of the necroptosis effector, MLKL

Necroptosis is a lytic programmed cell death pathway with origins in innate immunity that is frequently dysregulated in inflammatory diseases. The terminal effector of the pathway, MLKL, is licensed to kill following phosphorylation of its pseudokinase domain by the upstream regulator, RIPK3 kinase. Phosphorylation provokes the unleashing of MLKL's N-terminal four-helix bundle (4HB or HeLo) domain, which binds and permeabilizes the plasma membrane to cause cell death. The precise mechanism by which the 4HB domain permeabilizes membranes, and how the mechanism differs between species, remains unclear. Here, we identify the membrane binding epitope of mouse MLKL using NMR spectroscopy. Using liposome permeabilization and cell death assays, we validate K69 in the α3 helix, W108 in the α4 helix, and R137/Q138 in the first brace helix as crucial residues for necroptotic signaling. This epitope differs from the phospholipid binding site reported for human MLKL, which comprises basic residues primarily located in the α1 and α2 helices. In further contrast to human and plant MLKL orthologs, in which the α3-α4 loop forms a helix, this loop is unstructured in mouse MLKL in solution. Together, these findings illustrate the versatility of the 4HB domain fold, whose lytic function can be mediated by distinct epitopes in different orthologs.