Both Ligands and Macromolecular Crowders Preferentially Bind to Closed Conformations of Maltose Binding Protein.

In cellular environments, proteins not only interact with their specific partners but also encounter a high concentration of bystander macromolecules, or crowders. Nonspecific interactions with macromolecular crowders modulate the activities of proteins, but our knowledge about the rules of nonspecific interactions is still very limited. In previous work, we presented experimental evidence that macromolecular crowders acted competitively in inhibiting the binding of maltose binding protein (MBP) with its ligand maltose. Competition between a ligand and an inhibitor may result from binding to either the same site or different conformations of the protein. Maltose binds to the cleft between two lobes of MBP, and in a series of mutants, the affinities increased with an increase in the extent of lobe closure. Here we investigated whether macromolecular crowders also have a conformational or site preference when binding to MBP. The affinities of a polymer crowder, Ficoll70, measured by monitoring tryptophan fluorescence were 3-6-fold higher for closure mutants than for wild-type MBP. Competition between the ligand and crowder, as indicated by fitting of titration data and directly by nuclear magnetic resonance spectroscopy, and their similar preferences for closed MBP conformations further suggest the scenario in which the crowder, like maltose, preferentially binds to the interlobe cleft of MBP. Similar observations were made for bovine serum albumin as a protein crowder. Conformational and site preferences in MBP-crowder binding allude to the paradigm that nonspecific interactions can possess hallmarks of molecular recognition, which may be essential for intracellular organizations including colocalization of proteins and liquid-liquid phase separation.

Structure and Dynamics of the Huntingtin Exon-1 N-Terminus: A Solution NMR Perspective.

Many neurodegenerative diseases are characterized by misfolding and aggregation of an expanded polyglutamine tract (polyQ). Huntington's Disease, caused by expansion of the polyQ tract in exon 1 of the Huntingtin protein (Htt), is associated with aggregation and neuronal toxicity. Despite recent structural progress in understanding the structures of amyloid fibrils, little is known about the solution states of Htt in general, and about molecular details of their transition from soluble to aggregation-prone conformations in particular. This is an important question, given the increasing realization that toxicity may reside in soluble conformers. This study presents an approach that combines NMR with computational methods to elucidate the structural conformations of Htt Exon 1 in solution. Of particular focus was Htt's N17 domain sited N-terminal to the polyQ tract, which is key to enhancing aggregation and modulate Htt toxicity. Such in-depth structural study of Htt presents a number of unique challenges: the long homopolymeric polyQ tract contains nearly identical residues, exon 1 displays a high degree of conformational flexibility leading to a scaling of the NMR chemical shift dispersion, and a large portion of the backbone amide groups are solvent-exposed leading to fast hydrogen exchange and causing extensive line broadening. To deal with these problems, NMR assignment was achieved on a minimal Htt exon 1, comprising the N17 domain, a polyQ tract of 17 glutamines, and a short hexameric polyProline region that does not contribute to the spectrum. A pH titration method enhanced this polypeptide's solubility and, with the aid of ≤5D NMR, permitted the full assignment of N17 and the entire polyQ tract. Structural predictions were then derived using the experimental chemical shifts of the Htt peptide at low and neutral pH, together with various different computational approaches. All these methods concurred in indicating that low-pH protonation stabilizes a soluble conformation where a helical region of N17 propagates into the polyQ region, while at neutral pH both N17 and the polyQ become largely unstructured-thereby suggesting a mechanism for how N17 regulates Htt aggregation.

Establishing resolution-improved NMR spectroscopy in high magnetic fields with unknown spatiotemporal variations.

A half-century quest for higher magnetic fields has been an integral part of the progress undergone in the Nuclear Magnetic Resonance (NMR) study of materials' structure and dynamics. Because 2D NMR relies on systematic changes in coherences' phases as a function of an encoding time varied over a series of independent experiments, it generally cannot be applied in temporally unstable fields. This precludes most NMR methods from being used to characterize samples situated in hybrid or resistive magnets that are capable of achieving extremely high magnetic field strength. Recently, "ultrafast" NMR has been developed into an effective and widely applicable methodology enabling the acquisition of a multidimensional NMR spectrum in a single scan; it can therefore be used to partially mitigate the effects of temporally varying magnetic fields. Nevertheless, the strong interference of fluctuating fields with the spatial encoding of ultrafast NMR still severely restricts measurement sensitivity and resolution. Here, we introduce a strategy for obtaining high resolution NMR spectra that exploits the immunity of intermolecular zero-quantum coherences (iZQCs) to field instabilities and inhomogeneities. The spatial encoding of iZQCs is combined with a J-modulated detection scheme that removes the influence of arbitrary field inhomogeneities during acquisition. This new method can acquire high-resolution one-dimensional NMR spectra in large inhomogeneous and fluctuating fields, and it is tested with fields experimentally modeled to mimic those of resistive and resistive-superconducting hybrid magnets.

Shift-driven modulations of spin-echo signals.

Since the pioneering works of Carr-Purcell and Meiboom-Gill [Carr HY, Purcell EM (1954) Phys Rev 94:630; Meiboom S, Gill D (1985) Rev Sci Instrum 29:688], trains of π-pulses have featured amongst the main tools of quantum control. Echo trains find widespread use in nuclear magnetic resonance spectroscopy (NMR) and imaging (MRI), thanks to their ability to free the evolution of a spin-1/2 from several sources of decoherence. Spin echoes have also been researched in dynamic decoupling scenarios, for prolonging the lifetimes of quantum states or coherences. Inspired by this search we introduce a family of spin-echo sequences, which can still detect site-specific interactions like the chemical shift. This is achieved thanks to the presence of weak environmental fluctuations of common occurrence in high-field NMR--such as homonuclear spin-spin couplings or chemical/biochemical exchanges. Both intuitive and rigorous derivations of the resulting "selective dynamical recoupling" sequences are provided. Applications of these novel experiments are given for a variety of NMR scenarios including determinations of shift effects under inhomogeneities overwhelming individual chemical identities, and model-free characterizations of chemically exchanging partners.

Reducing acquisition times in multidimensional NMR with a time-optimized Fourier encoding algorithm.

Speeding up the acquisition of multidimensional nuclear magnetic resonance (NMR) spectra is an important topic in contemporary NMR, with central roles in high-throughput investigations and analyses of marginally stable samples. A variety of fast NMR techniques have been developed, including methods based on non-uniform sampling and Hadamard encoding, that overcome the long sampling times inherent to schemes based on fast-Fourier-transform (FFT) methods. Here, we explore the potential of an alternative fast acquisition method that leverages a priori knowledge, to tailor polychromatic pulses and customized time delays for an efficient Fourier encoding of the indirect domain of an NMR experiment. By porting the encoding of the indirect-domain to the excitation process, this strategy avoids potential artifacts associated with non-uniform sampling schemes and uses a minimum number of scans equal to the number of resonances present in the indirect dimension. An added convenience is afforded by the fact that a usual 2D FFT can be used to process the generated data. Acquisitions of 2D heteronuclear correlation NMR spectra on quinine and on the anti-inflammatory drug isobutyl propionic phenolic acid illustrate the new method's performance. This method can be readily automated to deal with complex samples such as those occurring in metabolomics, in in-cell as well as in in vivo NMR applications, where speed and temporal stability are often primary concerns.

Spectra-Based Machine Learning for Predicting the Statistical Interaction Properties of CO Adsorbates on Surface.

Theoretical analyses of small-molecule adsorption on heterogeneous catalyst surfaces often rely on simplified models of molecular adsorption with the most favorable configuration. Given that real-world experimental tests frequently entail multiple molecules interacting with the surface, there is a pressing need for a comprehensive multimolecule adsorption model to bridge the gap between theory and experiment. Using machine learning, we predict the average values of important adsorption properties from conformationally averaged, calculated infrared and Raman spectra and compare these values to those theoretically derived from the conformationally averaged ensemble. Remarkably, our approach yields excellent predictions even when faced with large and indeterminate numbers of surface molecules. These quantitative spectra-averaged property relationships provide a theoretical framework for extracting key interaction properties from the spectra of real chemical environments.

Ultrafast NMR T1 relaxation measurements: probing molecular properties in real time.

The longitudinal relaxation properties of NMR active nuclei carry useful information about the site-specific chemical environments and about the mobility of molecular fragments. Molecular mobility is in turn a key parameter reporting both on stable properties, such as size, as well as on dynamic ones, such as transient interactions and irreversible aggregation. In order to fully investigate the latter, a fast sampling of the relaxation parameters of transiently formed molecular species may be needed. Nevertheless, the acquisition of longitudinal relaxation data is typically slow, being limited by the requirement that the time for which the nucleus relaxes be varied incrementally until a complete build-up curve is generated. Recently, a number of single-shot-inversion-recovery methods have been developed capable of alleviating this need; still, these may be challenged by either spectral resolution restrictions or when coping with very fast relaxing nuclei. Here, we present a new experiment to measure the T1s of multiple nuclear spins that experience fast longitudinal relaxation, while retaining full high-resolution chemical shift information. Good agreement is observed between T1s measured with conventional means and T1s measured using the new technique. The method is applied to the real-time investigation of the reaction between D-xylose and sodium borate, which is in turn elucidated with the aid of ancillary ultrafast and conventional 2D TOCSY measurements.

Machine Learning Descriptors for Data-Driven Catalysis Study.

Traditional trial-and-error experiments and theoretical simulations have difficulty optimizing catalytic processes and developing new, better-performing catalysts. Machine learning (ML) provides a promising approach for accelerating catalysis research due to its powerful learning and predictive abilities. The selection of appropriate input features (descriptors) plays a decisive role in improving the predictive accuracy of ML models and uncovering the key factors that influence catalytic activity and selectivity. This review introduces tactics for the utilization and extraction of catalytic descriptors in ML-assisted experimental and theoretical research. In addition to the effectiveness and advantages of various descriptors, their limitations are also discussed. Highlighted are both 1) newly developed spectral descriptors for catalytic performance prediction and 2) a novel research paradigm combining computational and experimental ML models through suitable intermediate descriptors. Current challenges and future perspectives on the application of descriptors and ML techniques to catalysis are also presented.

Proton-evolved local-field solid-state NMR studies of cytochrome b5 embedded in bicelles, revealing both structural and dynamical information.

Structural biology of membrane proteins has rapidly evolved into a new frontier of science. Although solving the structure of a membrane protein with atomic-level resolution is still a major challenge, separated local field (SLF) NMR spectroscopy has become an invaluable tool in obtaining structural images of membrane proteins under physiological conditions. Recent studies have demonstrated the use of rotating-frame SLF techniques to accurately measure strong heteronuclear dipolar couplings between directly bonded nuclei. However, in these experiments, all weak dipolar couplings are suppressed. On the other hand, weak heteronuclear dipolar couplings can be measured using laboratory-frame SLF experiments, but only at the expense of spectral resolution for strongly dipolar coupled spins. In the present study, we implemented two-dimensional proton-evolved local-field (2D PELF) pulse sequences using either composite zero cross-polarization (COMPOZER-CP) or windowless isotropic mixing (WIM) for magnetization transfer. These PELF sequences can be used for the measurement of a broad range of heteronuclear dipolar couplings, allowing for a complete mapping of protein dynamics in a lipid bilayer environment. Experimental results from magnetically aligned bicelles containing uniformly (15)N-labeled cytochrome b(5) are presented and theoretical analyses of the new PELF sequences are reported. Our results suggest that the PELF-based experimental approaches will have a profound impact on solid-state NMR spectroscopy of membrane proteins and other membrane-associated molecules in magnetically aligned bicelles.

Solid-state NMR reveals the hydrophobic-core location of poly(amidoamine) dendrimers in biomembranes.

Poly(amidoamine) (PAMAM) dendrimer nanobiotechnology shows great promise in targeted drug delivery and gene therapy. Because of the involvement of cell membrane lipids with the pharmacological activity of dendrimer nanomedicines, the interactions between dendrimers and lipids are of particular relevance to the pharmaceutical applications of dendrimers. In this study, solid-state NMR was used to obtain a molecular image of the complex of generation-5 (G5) PAMAM dendrimer with the lipid bilayer. Using (1)H radio frequency driven dipolar recoupling (RFDR) and (1)H magic angle spinning (MAS) nuclear Overhauser effect spectroscopy (NOESY) techniques, we show that dendrimers are thermodynamically stable when inserted into zwitterionic lipid bilayers. (14)N and (31)P NMR experiments on static samples and measurements of the mobility of C-H bonds using a 2D proton detected local field protocol under MAS corroborate these results. The localization of dendrimers in the hydrophobic core of lipid bilayers restricts the motion of bilayer lipid tails, with the smaller G5 dendrimer having more of an effect than the larger G7 dendrimer. Fragmentation of the membrane does not occur at low dendrimer concentrations in zwitterionic membranes. Because these results show that the amphipathic dendrimer molecule can be stably incorporated in the interior of the bilayer (as opposed to electrostatic binding at the surface), they are expected to be useful in the design of dendrimer-based nanobiotechnologies.

Induction of negative curvature as a mechanism of cell toxicity by amyloidogenic peptides: the case of islet amyloid polypeptide.

The death of insulin-producing beta-cells is a key step in the pathogenesis of type 2 diabetes. The amyloidogenic peptide Islet Amyloid Polypeptide (IAPP, also known as amylin) has been shown to disrupt beta-cell membranes leading to beta-cell death. Despite the strong evidence linking IAPP to the destruction of beta-cell membrane integrity and cell death, the mechanism of IAPP toxicity is poorly understood. In particular, the effect of IAPP on the bilayer structure has largely been uncharacterized. In this study, we have determined the effect of the amyloidogenic and toxic hIAPP(1-37) peptide and the nontoxic and nonamyloidogenic rIAPP(1-37) peptide on membranes by a combination of DSC and solid-state NMR spectroscopy. We also characterized the toxic but largely nonamyloidogenic rIAPP(1-19) and hIAPP(1-19) fragments. DSC shows that both amyloidogenic (hIAPP(1-37)) and largely nonamyloidogenic (hIAPP(1-19) and rIAPP(1-19)) toxic versions of the peptide strongly favor the formation of negative curvature in lipid bilayers, while the nontoxic full-length rat IAPP(1-37) peptide does not. This result was confirmed by solid-state NMR spectroscopy which shows that in bicelles composed of regions of high curvature and low curvature, nontoxic rIAPP(1-37) binds to the regions of low curvature while toxic rIAPP(1-19) binds to regions of high curvature. Similarly, solid-state NMR spectroscopy shows that the toxic rIAPP(1-19) peptide significantly disrupts the lipid bilayer structure, whereas the nontoxic rIAPP(1-37) does not have a significant effect. These results indicate IAPP may induce the formation of pores by the induction of excess membrane curvature and can be used to guide the design of compounds that can prevent the cell-toxicity of IAPP. This mechanism may be important to understand the toxicity of other amyloidogenic proteins. Our solid-state NMR results also demonstrate the possibility of using bicelles to measure the affinity of biomolecules for negatively or positively curved regions of the membrane, which we believe will be useful in a variety of biochemical and biophysical investigations related to the cell membrane.

Determining the effects of lipophilic drugs on membrane structure by solid-state NMR spectroscopy: the case of the antioxidant curcumin.

Curcumin is the active ingredient of turmeric powder, a natural spice used for generations in traditional medicines. Curcumin's broad spectrum of antioxidant, anticarcinogenic, antimutagenic, and anti-inflammatory properties makes it particularly interesting for the development of pharmaceutical compounds. Because of curcumin's various effects on the function of numerous unrelated membrane proteins, it has been suggested that it affects the properties of the bilayer itself. However, a detailed atomic-level study of the interaction of curcumin with membranes has not been attempted. A combination of solid-state NMR and differential scanning calorimetry experiments shows curcumin has a strong effect on membrane structure at low concentrations. Curcumin inserts deep into the membrane in a transbilayer orientation, anchored by hydrogen bonding to the phosphate group of lipids in a manner analogous to cholesterol. Like cholesterol, curcumin induces segmental ordering in the membrane. Analysis of the concentration dependence of the order parameter profile derived from NMR results suggests curcumin forms higher order oligomeric structures in the membrane that span and likely thin the bilayer. Curcumin promotes the formation of the highly curved inverted hexagonal phase, which may influence exocytotic and membrane fusion processes within the cell. The experiments outlined here show promise for understanding the action of other drugs such as capsaicin in which drug-induced alterations of membrane structure have strong pharmacological effects.

Huntingtin's N-Terminus Rearrangements in the Presence of Membranes: A Joint Spectroscopic and Computational Perspective.

Huntington's disease is a neurodegenerative disorder resulting from an expanded polyglutamine (polyQ) repeat of the Huntingtin (Htt) protein. Affected tissues often contain aggregates of the N-terminal Htt exon 1 (Htt-Ex1) fragment. The N-terminal N17 domain proximal to the polyQ tract is key to enhance aggregation and modulate Htt toxicity. Htt-Ex1 is intrinsically disordered, yet it has been postulated that under physiological conditions membranes induce the N17 to adopt an α-helical structure, which then plays a key role in regulating Htt protein aggregation. The present study leverages the recently available assignment of NMR peaks in an N17Q17 construct, in order to provide a look into the changes occurring in vitro upon exposing this fragment to various brain extract fragments as well as to synthetic bilayers. Residue-specific changes were observed by 3D HNCO NMR, whose nature was further clarified with ancillary CD and aggregation studies, as well as with molecular dynamic calculations. From this combination of measurements and computations, a unified picture emerges, whereby transient structures consisting of α-helices spanning a fraction of the N17 residues form during N17Q17-membrane interactions. These interactions are fairly dynamic, but they qualitatively mimic more rigid variants that have been discussed in the literature. The nature of these interactions and their potential influence on the aggregation process of these kinds of constructs under physiological conditions are briefly assessed.

Single-Scan High-Resolution 2-D $J$ -Resolved Spectroscopy in Inhomogeneous Magnetic Fields.

OBJECTIVE: A method is proposed to obtain high-resolution 2-D -resolved nuclear magnetic resonance (NMR) spectra in inhomogeneous magnetic fields. METHODS: The proposed experiment enables the acquisition of an entire 2-D spectrum in a single scan by utilizing intermolecular double-quantum coherences and the spatial encoding of NMR observables. RESULTS: Chemical shifts, coupling constants, and multiplet patterns are recovered even when field inhomogeneities are severe enough to completely obscure conventional NMR spectra. After intentional deshimming to yield inhomogeneous magnetic fields, the method was demonstrated on ethyl 3-bromoproprionate in acetone and on a complex mixture of organic compounds. To illustrate the technique's applicability to biological samples with intrinsic magnetic field inhomogeneities arising from macroscopic magnetic susceptibility variations, we performed the experiment on a pig bone marrow sample. CONCLUSION: Our results show that the new method is a fast and effective tool for studying complex chemical mixtures and biological tissues. SIGNIFICANCE: The method could potentially be useful for real-time in vivo NMR studies.

A fast approach to 3D HSQC-based spectroscopy based on a Fourier phase encoding of pre-targeted resonances.

Multidimensional Nuclear Magnetic Resonance (NMR) provides a unique window into structure and dynamics at an atomic level. Traditionally, given the scan-by-scan time modulation involved in these experiments, the duration of nD NMR increases exponentially with spectral dimensionality. In addition, acquisition times increase as the number of spectral elements being sought in each indirect domain - given by the ratio between the spectral bandwidth being targeted and the resolution desired. These long sampling times can be substantially reduced by exploiting information that is often available from lower-dimensionality acquisitions. This work presents a novel approach that exploits previous 2D information to speed up the acquisition of 3D spectra, based on what we denote as a Time-Optimized FouriEr Encoding (TOFEE) of pre-targeted peaks. Such 3D TOFEE experiments, which present points in common with Hadamard-encoded 3D acquisitions, do not necessarily require more scans than their 2D counterparts. This is here demonstrated based on extensions of 2D Heteronuclear Single-quantum Coherence (HSQC) experiments, to 3D HSQC-TOCSY or 3D HSQC-NOESY acquisitions. The theoretical basis of this new approach is given, and experimental demonstrations are presented on small molecule and protein-based model systems.

High-resolution heteronuclear multi-dimensional NMR spectroscopy in magnetic fields with unknown spatial variations.

Heteronuclear NMR spectroscopy is an extremely powerful tool for determining the structures of organic molecules and is of particular significance in the structural analysis of proteins. In order to leverage the method's potential for structural investigations, obtaining high-resolution NMR spectra is essential and this is generally accomplished by using very homogeneous magnetic fields. However, there are several situations where magnetic field distortions and thus line broadening is unavoidable, for example, the samples under investigation may be inherently heterogeneous, and the magnet's homogeneity may be poor. This line broadening can hinder resonance assignment or even render it impossible. We put forth a new class of pulse sequences for obtaining high-resolution heteronuclear spectra in magnetic fields with unknown spatial variations based on distant dipolar field modulations. This strategy's capabilities are demonstrated with the acquisition of high-resolution 2D gHSQC and gHMBC spectra. These sequences' performances are evaluated on the basis of their sensitivities and acquisition efficiencies. Moreover, we show that by encoding and decoding NMR observables spatially, as is done in ultrafast NMR, an extra dimension containing J-coupling information can be obtained without increasing the time necessary to acquire a heteronuclear correlation spectrum. Since the new sequences relax magnetic field homogeneity constraints imposed upon high-resolution NMR, they may be applied in portable NMR sensors and studies of heterogeneous chemical and biological materials.

A proton spin diffusion based solid-state NMR approach for structural studies on aligned samples.

Rapidly expanding research on nonsoluble and noncrystalline chemical and biological materials necessitates sophisticated techniques to image these materials at atomic-level resolution. Although their study poses a formidable challenge, solid-state NMR is a powerful tool that has demonstrated application to the investigation of their molecular architecture and functioning. In particular, 2D separated-local-field (SLF) spectroscopy is increasingly applied to obtain high-resolution molecular images of these materials. However, despite the common use of SLF experiments in the structural studies of a variety of aligned molecules, the lack of a resonance assignment approach has been a major disadvantage. As a result, solid-state NMR studies have mostly been limited to aligned systems that are labeled with an isotope at a single site. Here, we demonstrate an approach for resonance assignment through a controlled reintroduction of proton spin diffusion in the 2D proton-evolved-local-field (PELF) pulse sequence. Experimental results and simulations suggest that the use of spin diffusion also enables the measurement of long-range heteronuclear dipolar couplings that can be used as additional constraints in the structural and dynamical studies of aligned molecules. The new method is used to determine the de novo atomic-level resolution structure of a liquid crystalline material, N-(4-methoxybenzylidene)-4-butylaniline, and its use on magnetically aligned bicelles is also demonstrated. We expect this technique to also be valuable in the structural studies of functional molecules like columnar liquid crystals and other biomaterials.