NMR 1H, 13C, 15N backbone resonance assignments of wild-type human K-Ras and its oncogenic mutants G12D and G12C bound to GTP.

Human K-Ras protein, which is a member of the GTPase Ras family, hydrolyzes GTP to GDP and concomitantly converts from its active to its inactive state. It is a key oncoprotein, because several mutations, particularly those at residue position 12, occur with a high frequency in a wide range of human cancers. The K-Ras protein is therefore an important target for developing therapeutic anti-cancer agents. In this work we report the almost complete sequence-specific resonance assignments of wild-type and the oncogenic G12C and G12D mutants in the GTP-complexed active forms, including the functionally important Switch I and Switch II regions. These assignments serve as the basis for a comprehensive functional dynamics study of wild-type K-Ras and its G12 mutants.

DEEP Picker1D and Voigt Fitter1D: a versatile tool set for the automated quantitative spectral deconvolution of complex 1D-NMR spectra.

The quantitative deconvolution of 1D-NMR spectra into individual resonances or peaks is a key step in many modern NMR workflows as it critically affects downstream analysis and interpretation. Depending on the complexity of the NMR spectrum, spectral deconvolution can be a notable challenge. Based on the recent deep neural network DEEP Picker and Voigt Fitter for 2D NMR spectral deconvolution, we present here an accurate, fully automated solution for 1D-NMR spectral analysis, including peak picking, fitting, and reconstruction. The method is demonstrated for complex 1D solution NMR spectra showing excellent performance also for spectral regions with multiple strong overlaps and a large dynamic range whose analysis is challenging for current computational methods. The new tool will help streamline 1D-NMR spectral analysis for a wide range of applications and expand their reach toward ever more complex molecular systems and their mixtures.

Dynamic and Assembly Characteristics of Deep-Cavity Basket Acting as a Host for Inclusion Complexation of Mitoxantrone in Biotic and Abiotic Systems.

We describe the preparation, dynamic, assembly characteristics of vase-shaped basket 13- along with its ability to form an inclusion complex with anticancer drug mitoxantrone in abiotic and biotic systems. This novel cavitand has a deep nonpolar pocket consisting of three naphthalimide sides fused to a bicyclic platform at the bottom while carrying polar glycines at the top. The results of 1 H Nuclear Magnetic Resonance (NMR), 1 H NMR Chemical Exchange Saturation Transfer (CEST), Calorimetry, Hybrid Replica Exchange Molecular Dynamics (REMD), and Microcrystal Electron Diffraction (MicroED) measurements are in line with 1 forming dimer [12 ]6- , to be in equilibrium with monomers 1(R) 3- (relaxed) and 1(S) 3- (squeezed). Through simultaneous line-shape analysis of 1 H NMR data, kinetic and thermodynamic parameters characterizing these equilibria were quantified. Basket 1(R) 3- includes anticancer drug mitoxantrone (MTO2+ ) in its pocket to give stable binary complex [MTO⊂1]- (Kd =2.1 µM) that can be precipitated in vitro with UV light or pH as stimuli. Both in vitro and in vivo studies showed that the basket is nontoxic, while at a higher proportion with respect to MTO it reduced its cytotoxicity in vitro. With well-characterized internal dynamics and dimerization, the ability to include mitoxantrone, and biocompatibility, the stage is set to develop sequestering agents from deep-cavity baskets.

Thermodynamic Coupling of the tandem RRM domains of hnRNP A1 underlie its Pleiotropic RNA Binding Functions.

The functional properties of RNA-binding proteins (RBPs) require allosteric regulation through inter-domain communication. Despite the foundational importance of allostery to biological regulation, almost no studies have been conducted to describe the biophysical nature by which inter-domain communication manifests in RBPs. Here, we show through high-pressure studies with hnRNP A1 that inter-domain communication is vital for the unique stability of its N- terminal domain containing a tandem of RNA Recognition Motifs (RRMs). Despite high sequence similarity and nearly identical tertiary structures, the two RRMs exhibit drastically different stability under pressure. RRM2 unfolds completely under high-pressure as an individual domain, but when appended to RRM1, it remains stable. Variants in which inter-domain communication is disrupted between the tandem RRMs show a large decrease in stability under pressure. Carrying these mutations over to the full-length protein for in vivo experiments revealed that the mutations affected the ability of the disordered C-terminus to engage in protein-protein interactions and more importantly, they also influenced the RNA binding capacity. Collectively, this work reveals that thermodynamic coupling between the tandem RRMs of hnRNP A1 accounts for its allosteric regulatory functions.

Excited-state observation of active K-Ras reveals differential structural dynamics of wild-type versus oncogenic G12D and G12C mutants.

Despite the prominent role of the K-Ras protein in many different types of human cancer, major gaps in atomic-level information severely limit our understanding of its functions in health and disease. Here, we report the quantitative backbone structural dynamics of K-Ras by solution nuclear magnetic resonance spectroscopy of the active state of wild-type K-Ras bound to guanosine triphosphate (GTP) nucleotide and two of its oncogenic P-loop mutants, G12D and G12C, using a new nanoparticle-assisted spin relaxation method, relaxation dispersion and chemical exchange saturation transfer experiments covering the entire range of timescales from picoseconds to milliseconds. Our combined experiments allow detection and analysis of the functionally critical Switch I and Switch II regions, which have previously remained largely unobservable by X-ray crystallography and nuclear magnetic resonance spectroscopy. Our data reveal cooperative transitions of K-Ras·GTP to a highly dynamic excited state that closely resembles the partially disordered K-Ras·GDP state. These results advance our understanding of differential GTPase activities and signaling properties of the wild type versus mutants and may thus guide new strategies for the development of therapeutics.

ARCHE-NOAH: NMR supersequence with five different CEST experiments for studying protein conformational dynamics.

An NMR NOAH-supersequence is presented consisting of five CEST experiments for studying protein backbone and side-chain dynamics by 15N-CEST, carbonyl-13CO-CEST, aromatic-13Car-CEST, 13Cα-CEST, and methyl-13Cmet-CEST. The new sequence acquires the data for these experiments in a fraction of the time required for the individual experiments, saving over four days of NMR time per sample.

NOAH-(15N/13C)-CEST NMR supersequence for dynamics studies of biomolecules.

An NMR supersequence is introduced for the rapid acquisition of 15N-CEST and methyl-13C-CEST experiments in the same pulse sequence for applications to proteins. The high sensitivity and accuracy allows the simultaneous quantitative characterization of backbone and side-chain dynamics on the millisecond timescale ideal for routine screening for alternative protein states.

Fundamental and practical aspects of machine learning for the peak picking of biomolecular NMR spectra.

Rapid progress in machine learning offers new opportunities for the automated analysis of multidimensional NMR spectra ranging from protein NMR to metabolomics applications. Most recently, it has been demonstrated how deep neural networks (DNN) designed for spectral peak picking are capable of deconvoluting highly crowded NMR spectra rivaling the facilities of human experts. Superior DNN-based peak picking is one of a series of critical steps during NMR spectral processing, analysis, and interpretation where machine learning is expected to have a major impact. In this perspective, we lay out some of the unique strengths as well as challenges of machine learning approaches in this new era of automated NMR spectral analysis. Such a discussion seems timely and should help define common goals for the NMR community, the sharing of software tools, standardization of protocols, and calibrate expectations. It will also help prepare for an NMR future where machine learning and artificial intelligence tools will be common place.

DEEP picker is a deep neural network for accurate deconvolution of complex two-dimensional NMR spectra.

The analysis of nuclear magnetic resonance (NMR) spectra for the comprehensive and unambiguous identification and characterization of peaks is a difficult, but critically important step in all NMR analyses of complex biological molecular systems. Here, we introduce DEEP Picker, a deep neural network (DNN)-based approach for peak picking and spectral deconvolution which semi-automates the analysis of two-dimensional NMR spectra. DEEP Picker includes 8 hidden convolutional layers and was trained on a large number of synthetic spectra of known composition with variable degrees of crowdedness. We show that our method is able to correctly identify overlapping peaks, including ones that are challenging for expert spectroscopists and existing computational methods alike. We demonstrate the utility of DEEP Picker on NMR spectra of folded and intrinsically disordered proteins as well as a complex metabolomics mixture, and show how it provides access to valuable NMR information. DEEP Picker should facilitate the semi-automation and standardization of protocols for better consistency and sharing of results within the scientific community.

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.

Increasing sensitivity and versatility in NMR supersequences with new HSQC-based modules.

The sensitivity-enhanced HSQC, as well as HSQC-TOCSY, experiments have been modified for incorporation into NOAH (NMR by Ordered Acquisition using 1H detection) supersequences, adding diversity for 13C and 15N modules. Importantly, these heteronuclear modules have been specifically tailored to preserve the magnetisation required for subsequent acquisition of other heteronuclear or homonuclear modules in a supersequence. In addition, we present protocols for optimally combining HSQC and HSQC-TOCSY elements within the same supersequences, yielding high-quality 2D spectra suitable for structure characterisation but with greatly reduced experiment durations. We further demonstrate that these time savings can translate to increased detection sensitivity per unit time.

From Selection to Instruction and Back: Competing Conformational Selection and Induced Fit Pathways in Abiotic Hosts.

Two limiting cases of molecular recognition, induced fit (IF) and conformational selection (CS), play a central role in allosteric regulation of natural systems. The IF paradigm states that a substrate "instructs" the host to change its shape after complexation, while CS asserts that a guest "selects" the optimal fit from an ensemble of preexisting host conformations. With no studies that quantitatively address the interplay of two limiting pathways in abiotic systems, we herein and for the first time describe the way by which twisted capsule M-1, encompassing two conformers M-1(+) and M-1(-), trap CX4 (X=Cl, Br) to give CX4 ⊂M-1(+) and CX4 ⊂M-1(-), with all four states being in thermal equilibrium. With the assistance of 2D EXSY, we found that CBr4 would, at its lower concentrations, bind M-1 via a M-1(+)→M-1(-)→CBr4 ⊂M-1(-) pathway corresponding to conformational selection. For M-1 complexing CCl4 though, data from 2D EXSY measurements and 1D NMR line-shape analysis suggested that lower CCl4 concentrations would favor CS while the IF pathway prevailed at higher proportions of the guest. Since CS and IF are not mutually exclusive, we reason that our work sets the stage for characterizing the dynamics of a wide range of already existing hosts to broaden our fundamental understanding of their action. The objective is to master the way in which encapsulation takes place for designing novel and allosteric sequestering agents, catalysts and chemosensors akin to those found in nature.

2D NMR-Based Metabolomics with HSQC/TOCSY NOAH Supersequences.

Sensitivity-improved versions of two-dimensional (2D) 13C-1H HSQC (heteronuclear single quantum coherence) and HSQC-TOCSY (HSQC-total correlation spectroscopy) NMR experiments optimized for small biological molecules and their complex mixtures encountered in metabolomics are presented that preserve the magnetization of 1H spins not directly attached to 13C spins. This allows (i) the application of rapid acquisition techniques to substantially shorten measurement time and (ii) their incorporation into supersequences (NOAH-NMR by ordered acquisition using 1H detection) for the compact acquisition of multiple 2D NMR data sets with significant gains in sensitivity, resolution, and/or time. The new pulse sequences, which are demonstrated for both metabolite model mixtures and mouse urine, offer an attractive approach for the efficient measurement of multiple 2D NMR spectra (HSQCsi and/or HSQCsi-TOCSY and TOCSY) of metabolomics samples in a single experiment for the accurate and comprehensive identification and quantitation of metabolites. These new methods bring to bear the advantages of 2D NMR to metabolomics studies with larger cohorts of samples.

4,15-Dimethyl-7,12-diazo-niatri-cyclo-[10.4.0.02,7]hexa-deca-1(12),2,4,6,13,15-hexa-ene dibromide monohydrate.

The title compound, C16H20N2 2+·2Br-·H2O (1) is a member of the class of compounds called viologens. Viologens are quaternary salts of di-pyridyls and are especially useful as redox indicators as a result of their large negative one-electron reduction potentials. Compound 1 consists of a dication composed of a pair of 4-methyl-pyridine rings mutually joined at the 2-position, with a dihedral angle between the pyridine rings of 62.35 (4)°. In addition, the rings are tethered via the pyridine nitro-gen atoms by a tetra-methyl-ene bridge. Charge balance is provided by a pair of bromide anions, which are hydrogen bonded to a single water mol-ecule [D O⋯Br = 3.3670 (15) and 3.3856 (15) Å]. The crystal structure of 1, details of an improved synthesis, and a full analysis of its NMR spectra are presented.

Extreme Nonuniform Sampling for Protein NMR Dynamics Studies in Minimal Time.

NMR spectroscopy is an extraordinarily rich source of quantitative dynamics of proteins in solution using spin relaxation or chemical exchange saturation transfer (CEST) experiments. However, 15N-CEST measurements require prolonged multidimensional, so-called pseudo-3D HSQC experiments where the pseudo dimension is a radio frequency offset Δω of a weak 15N saturation field. Nonuniform sampling (NUS) approaches have the potential to significantly speed up these measurements, but they also carry the risk of introducing serious artifacts and the systematic optimization of nonuniform sampling schedules has remained elusive. It is demonstrated here how this challenge can be addressed by using fitted cross-peaks of a reference 2D HSQC experiment as footprints, which are subsequently used to reconstruct cross-peak amplitudes of a pseudo-3D data set as a function of Δω by a linear least-squares fit. It is shown for protein Im7 how the approach can yield highly accurate CEST profiles based on an absolutely minimally sampled (AMS) data set allowing a speed-up of a factor 20-30. Spectrum-specific optimized nonuniform sampling (SONUS) schemes based on the Cramer-Rao lower bound metric were critical to achieve such a performance, revealing also more general properties of optimal sampling schedules. This is the first systematic exploration and optimization of NUS schedules for the dramatic speed-up of quantitative multidimensional NMR measurements that minimize unwanted errors.

Functional protein dynamics on uncharted time scales detected by nanoparticle-assisted NMR spin relaxation.

Protein function depends critically on intrinsic internal dynamics, which is manifested in distinct ways, such as loop motions that regulate protein recognition and catalysis. Under physiological conditions, dynamic processes occur on a wide range of time scales from subpicoseconds to seconds. Commonly used NMR spin relaxation in solution provides valuable information on very fast and slow motions but is insensitive to the intermediate nanosecond to microsecond range that exceeds the protein tumbling correlation time. Presently, very little is known about the nature and functional role of these motions. It is demonstrated here how transverse spin relaxation becomes exquisitely sensitive to these motions at atomic resolution when studying proteins in the presence of nanoparticles. Application of this novel cross-disciplinary approach reveals large-scale dynamics of loops involved in functionally critical protein-protein interactions and protein-calcium ion recognition that were previously unobservable.

Real-Time Pure Shift HSQC NMR for Untargeted Metabolomics.

Sensitivity and resolution are key considerations for NMR applications in general and for metabolomics in particular, where complex mixtures containing hundreds of metabolites over a large range of concentrations are commonly encountered. There is a strong demand for advanced methods that can provide maximal information in the shortest possible time frame. Here, we present the optimization and application of the recently introduced 2D real-time BIRD 1H-13C HSQC experiment for NMR-based metabolomics of aqueous samples at 13C natural abundance. For mouse urine samples, it is demonstrated how this real-time pure shift sensitivity-improved heteronuclear single quantum correlation method provides broadband homonuclear decoupling along the proton detection dimension and thereby significantly improves spectral resolution in regions that are affected by spectral overlap. Moreover, the collapse of the scalar multiplet structure of cross-peaks leads to a sensitivity gain of about 40-50% over a traditional 2D HSQC-SI experiment. The experiment works well over a range of magnetic field strengths and is particularly useful when resonance overlap in crowded regions of the HSQC spectra hampers accurate metabolite identification and quantitation.

Quantitative Binding Behavior of Intrinsically Disordered Proteins to Nanoparticle Surfaces at Individual Residue Level.

The quantitative and predictive understanding how intrinsically disordered proteins (IDPs) interact with engineered nanoparticles has potentially important implications for new therapeutics as well as nanotoxicology. Based on a recently developed solution 15 N NMR relaxation approach, the interactions between four representative IDPs with silica nanoparticles are reported at atomic detail. Each IDP possesses distinct binding modes, which can be quantitatively explained by the local amino-acid residue composition using a "free residue interaction model". The model was parameterized using the binding affinities of free proteinogenic amino acids along with long-range effects, derived by site-specific mutagenesis, that exponentially scale with distance along the primary sequence. The model, which is accessible through a web server, can be applied to predict the residue-specific binding affinities of a large number of IDPs.

Differential Conformational Dynamics Encoded by the Linker between Quasi RNA Recognition Motifs of Heterogeneous Nuclear Ribonucleoprotein H.

Members of the heterogeneous nuclear ribonucleoprotein (hnRNP) F/H family are multipurpose RNA binding proteins that participate in most stages of RNA metabolism. Despite having similar RNA sequence preferences, hnRNP F/H proteins function in overlapping and, in some cases, distinct cellular processes. The domain organization of hnRNP F/H proteins is modular, consisting of N-terminal tandem quasi-RNA recognition motifs (F/HqRRM1,2) and a third C-terminal qRRM3 embedded between glycine-rich repeats. The tandem qRRMs are connected through a 10-residue linker, with several amino acids strictly conserved between hnRNP H and F. A significant difference occurs at position 105 of the linker, where hnRNP H contains a proline and hnRNP F an alanine. To investigate the influence of P105 on the conformational properties of hnRNP H, we probed the structural dynamics of its HqRRM1,2 domain with X-ray crystallography, NMR spectroscopy, and small-angle X-ray scattering. The collective results best describe that HqRRM1,2 exists in a conformational equilibrium between compact and extended structures. The compact structure displays an electropositive surface formed at the qRRM1-qRRM2 interface. Comparison of NMR relaxation parameters, including Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion, between HqRRM1,2 and FqRRM1,2 indicates that FqRRM1,2 primarily adopts a more extended and flexible conformation. Introducing the P105A mutation into HqRRM1,2 alters its conformational dynamics to favor an extended structure. Thus, our work demonstrates that the linker compositions confer different structural properties between hnRNP F/H family members that might contribute to their functional diversity.

Resonance assignments of wild-type and two cysteine-free variants of the four-helix bundle protein, Rop.

Repressor of primer (Rop, or ROM, RNA I modulator) is a 63 amino acid four-helix bundle protein that exists in solution as an anti-parallel homodimer. This protein has been extensively studied, including by X-ray crystallography, NMR, rational design, and combinatorial mutagenesis. Previous NMR experiments with wild-type Rop were carried out at pH 2.3 and pH 6.3. In this paper, we report complete N-H backbone assignments for three variants of Rop under the same pH 6.3 conditions: wild-type Rop; a cysteine-free pseudo-wild type variant (C38A C52V); and a core-repacked variant of the Cys-free variant (T19V L41V C38A C52V). These assignments enable functional and dynamic studies of wild-type and Cys-free variants of Rop.