Preparation and characterization of β-sitosterol/β-cyclodextrin crystalline inclusion complexes

Protein-ligand interactions lie at the heart of most biological and medical processes. To lay the groundwork for a mechanistic understanding of complex biological networks, a detailed description of the associated proteins, their roles, and their interaction partners is essential. Furthermore, a detailed description of protein-ligand interactions is of pharmaceutical interest, as small molecules targeting proteins constitute the basis for the treatment of numerous medical conditions. In this thesis, we used nuclear magnetic resonance (NMR) spectroscopy to probe the conformational properties of biologically and pharmaceutically essential proteins, either alone or complexed with small molecules, to reveal the mechanistic grounds of these interactions. The first chapter entails the structural investigation of Tumor necrosis factor-alpha (TNFα) by NMR spectroscopy. TNFα is a homotrimeric protein that enjoys tremendous scientific and pharmaceutical interest due to its pivotal role in the human immune response. However, its overexpression leads to numerous chronic inflammatory diseases. Studying the interaction between TNFα and small molecular inhibitors is thus of utmost importance if better cures for these diseases are to be found. Here, we investigated active and inhibited forms of TNFα in solution by NMR spectroscopy and showed that TNFα exhibits significant conformational exchange, especially in the receptor binding site and the trimer interface, which is crucial for its biological activity. Inhibition of TNFα by perturbing the trimer interface, either by mutagenesis or by targeting it with small molecules, does not lead to disruption of the postulated trimer in solution. Instead, it induces a significant increase in the conformational dynamics of TNFα propagating from the trimer interface to the receptor-binding site. Therefore, we propose that an allosteric dynamic coupling between the trimer interface and the active site mediates inhibition. This provides novel insights into the mechanisms of TNFα inhibition, which in turn may lead to the development of better-suited drug assays against this highly important molecule. The second chapter presents the study of alpha acid glycoprotein-1 (AGP1) by NMR. The heavily glycosylated AGP1 is one of the two most abundant human serum proteins and binds various metabolites as well as, perhaps most interestingly from a pharmaceutical perspective, many administered drugs. Understanding the interaction between AGP1 and small molecules on a molecular level in addition to revealing the yet unclear impact of the appended glycans in this process is thus of great importance - as drug binding to plasma proteins modulates their pharmacokinetics and pharmacodynamics. In this thesis, efficient protocols were developed which enabled us to shed light on the influence of glycosylation on the structure of AGP1 and to characterize its ligand binding at a level of detail which had not yet been achieved. We showed that glycosylation affects the protein conformation in the vicinity of the glycosylation site, and provide evidence for a conformational rearrangement upon binding of small molecules. By giving these novel insights, our results contribute to the functional understanding of AGP1 and more broadly to the relatively unexplored class of glycoproteins. The third chapter discusses the combination of our measured NMR data (presented in chapters one and two) with DNA-encoded chemical libraries (DECL) in drug discovery. DECL allows for the efficient identification of potential small molecule binders, while our concomitant NMR data provide the framework for assisting both the validation of ‘hits’ and the optimization process. We could confirm interactions between TNFα or AGP1 and binders identified by DECL. Here, the first application of this approach for drug discovery for TNFα and AGP1 is presented. In summary, our study contributes to a better understanding of two highly relevant proteins: AGP1 and TNFα. The data presented provides original insights into the inhibition mechanisms of small molecules and revealed the importance of conformational dynamics in these processes. Finally, our results will add a new aspect to the complex process of rational drug development, which will ultimately benefit many patients affected by diverse medical conditions.

Preparation, characterization and photochemistry of 4,4′-diacetamidostilbene and its β-cyclodextrin inclusion complex

A nuclear magnetic resonance advance. Imaging fluorinated anesthetics in the brain.

Detailed knowledge of the structure of bio molecules with atomic resolution is essential for the understanding of their function. Moreover the identification and quantification of their dynamic processes are important, as they are the origin of molecular functionalities. Different spectroscopic methods like X-ray crystallography (limited to structure elucidation, no dynamics), mass spectroscopy, electron spin resonance (EPR) and nuclear magnetic resonance (NMR) spectroscopy can deliver this detailed structural information. Especially NMR spectroscopy has found its application in the identification of dynamic processes. This thesis was focused on the characterization of dynamic processes, the structure elucidation of natural products available in nanograms and the synthesis of lanthanide chelating tags for the study of protein-ligand and protein-protein interactions in solution. The thesis is divided into three chapters addressing a specific task of the mentioned topic. A: The influences of different donors and linkers on lanthanide chelating tags were investigated. A 4S-Tetramethylcyclen was used as enantiomerically pure core molecule. The side chains were based on enantiopure lactic acid derivatives. The carboxylic acids of lactic acid were transformed into different functional groups like thiols, nitrogens, and carbonyl. These different donor groups are expected to change the magnetic susceptibility tensor of the lanthanide cation in complex with the synthesized tags. Special protection protocols for the introduction of heteroatoms are presented. On this basis also two new linkers were introduced. These linkers bind in a selective way to cysteins on a protein surface as thioethers. The alpha-bromoketones are very selective for the coupling to cysteins, nevertheless they have a tendency to hydrolyse under Lewis acidic conditions. Vinylsulfones require harsher tagging conditions but they are much more stable against hydrolysis. All new tags were attached to proteins and tested as PCS reagents in protein NMR spectroscopy. B: The effects of para-substituents on the rotation barrier of 2,2«-propyl and 2,2«-butyl-bridged biphenyls were studied by dynamic NMR spectroscopy and dynamic HPLC measurements. Gibbs free activation energies of the rotation about the central biphenyl bond were estimated by variable temperature 1H-NMR experiments for the propyl bridged biphenyl. The resulting data were correlated to Hammett-parameters ?P as a measure of electron donor and acceptor strength. It was demonstrated that the electronic effects influence the activation barrier significantly, whereas sterics had only minor influence. Rate constants were calculated from line shape analysis and analysed by Eyring plots to calculate the entropic and enthalpic contributions. Thermodynamic data for the butyl-bridged biphenyls were directly obtained from dynamic HPLC chromatograms. DFT calculations delivered different transition states for the two series of biphenyls. The calculation of the activation parameters showed a similar trend and therefore the model is validated. The differences in the enthalpic and entropic contributions between HPLC, NMR and DFT calculations are method dependent, which was proven by changes of the solvent in NMR experiments that led to alteration of these contributions. C: The identification and total synthesis of a novel methylated lipid antigen (mLPA) was performed. The presented mLPA shows potent inhibition properties against human leukaemia. A combination of extraction protocols, activation essays and HPLC-MS measurements were used to identify the different antigen molecules from cell extracts. Three different candidates were identified. MS-MS experiments delivered structural insights, which were further confirmed by NMR spectroscopy and allowed the characterization of two of these structures. Total syntheses of the identified structures were performed in 6 linear steps. The high biological activity of the synthesized structures corroborated the identity of the active molecule.

Nuclear magnetic resonance (NMR) spectroscopy has been used extensively since the 1960’s to study phase transformations. When Lippmaa et al. (1980) presented the first significant high-resolution solid-state NMR spectroscopic study of minerals, the study of structural phase transitions by NMR was a mature field, appearing primarily in the physics literature (e.g., Blinc 1981; Rigamonti 1984). The sensitivity of NMR spectroscopy to short-range structure (first- and second-coordination spheres) and low-frequency dynamics (i.e., frequencies much lower than the thermal vibrations of atoms) make it useful for determining changes in the structure and dynamics of solids that occur near phase transitions. This combination of characteristic time- and distance-scales is not easily accessible by other techniques. Widely studied phase transformations include order-disorder and displacive transitions in compounds with perovskite, antifluorite, β-K2SO4 (A2BX4), KH2PO4 (“KDP”), and other structure types, including some mineral phases (e.g., colemanite; Theveneau and Papon 1976). These studies used primarily single-crystal techniques and were mostly limited to phases that exhibit high symmetry and possess one crystallographic site for the nucleus studied. In some cases, the NMR data can help distinguish order-disorder from purely displacive transition mechanisms. Also, careful measurement of NMR relaxation rates provides information on the spectral density at low frequencies, which reflects softening lattice vibrations or freezing-in of rotational disorder modes. Many phase transitions interesting to mineralogists became accessible to NMR spectroscopy in the late 1980’s with the commercial availability of magic-angle-spinning (MAS) NMR probe assemblies capable of operation at extended temperatures (up to about 600°C) and the development of high-temperature NMR capability at Stanford (Stebbins 1995b). These technical advances enabled many of the structural transitions that occur in minerals to be studied in situ by NMR, including those in phases for which large single crystals are not available. MAS-NMR …

Solid-state nuclear magnetic resonance (NMR) spectroscopy is an atomic-level method used to determine the chemical structure, three-dimensional structure, and dynamics of solids and semi-solids. This Primer summarizes the basic principles of NMR as applied to the wide range of solid systems. The fundamental nuclear spin interactions and the effects of magnetic fields and radiofrequency pulses on nuclear spins are the same as in liquid-state NMR. However, because of the anisotropy of the interactions in the solid state, the majority of high-resolution solid-state NMR spectra is measured under magic-angle spinning (MAS), which has profound effects on the types of radiofrequency pulse sequences required to extract structural and dynamical information. We describe the most common MAS NMR experiments and data analysis approaches for investigating biological macromolecules, organic materials, and inorganic solids. Continuing development of sensitivity-enhancement approaches, including 1H-detected fast MAS experiments, dynamic nuclear polarization, and experiments tailored to ultrahigh magnetic fields, is described. We highlight recent applications of solid-state NMR to biological and materials chemistry. The Primer ends with a discussion of current limitations of NMR to study solids, and points to future avenues of development to further enhance the capabilities of this sophisticated spectroscopy for new applications.

The Natural Products Magnetic Resonance Database (NP-MRD) is a comprehensive, freely available electronic resource for the deposition, distribution, searching and retrieval of nuclear magnetic resonance (NMR) data on natural products, metabolites and other biologically derived chemicals. NMR spectroscopy has long been viewed as the ‘gold standard’ for the structure determination of novel natural products and novel metabolites. NMR is also widely used in natural product dereplication and the characterization of biofluid mixtures (metabolomics). All of these NMR applications require large collections of high quality, well-annotated, referential NMR spectra of pure compounds. Unfortunately, referential NMR spectral collections for natural products are quite limited. It is because of the critical need for dedicated, open access natural product NMR resources that the NP-MRD was funded by the National Institute of Health (NIH). Since its launch in 2020, the NP-MRD has grown quickly to become the world's largest repository for NMR data on natural products and other biological substances. It currently contains both structural and NMR data for nearly 41,000 natural product compounds from >7400 different living species. All structural, spectroscopic and descriptive data in the NP-MRD is interactively viewable, searchable and fully downloadable in multiple formats. Extensive hyperlinks to other databases of relevance are also provided. The NP-MRD also supports community deposition of NMR assignments and NMR spectra (1D and 2D) of natural products and related meta-data. The deposition system performs extensive data enrichment, automated data format conversion and spectral/assignment evaluation. Details of these database features, how they are implemented and plans for future upgrades are also provided. The NP-MRD is available at https://np-mrd.org.

Nuclear magnetic resonance (NMR) spectroscopy is one of the most powerful analytical techniques available to biology. This review is an introduction to the potential of this method and is aimed at readers who have little or no experience in acquiring or analyzing NMR spectra. We focus on spectroscopic applications of the magnetic resonance effect, rather than imaging ones, and explain how various aspects of the NMR phenomenon make it a versatile tool with which to address a number of biological problems. Using detailed examples, we discuss the use of (1) H NMR spectroscopy in mixture analysis and metabolomics, the use of (13) C NMR spectroscopy in tracking isotopomers and determining the flux through metabolic pathways ('fluxomics') and the use of (31) P NMR spectroscopy in monitoring ATP generation and intracellular pH homeotasis in vivo. Further examples demonstrate how NMR spectroscopy can be used to probe the physical environment of a cell by measuring diffusion and the tumbling rates of individual metabolites and how it can determine macromolecular structures by measuring the bonds and distances which separate individual atoms. We finish by outlining some of the key challenges which remain in NMR spectroscopy and we highlight how recent advances-such as increased magnet field strengths, cryogenic cooling, microprobes and hyperpolarisation-are opening new avenues for today's biological NMR spectroscopists.

Chapter 1 of this thesis provides an overview of the structure and function of proteins as well as their investigation via NMR spectroscopy. Proteins are one of the most important building blocks of life. They are part of every organism and fulfill a variety of functions including, for example, the catalysis of many chemical reactions, which is the reason various processes in an organism become possible in the first place. Proteins are made up of amino acids, which are linked together via peptide bonds during the protein biosynthesis. The 22 proteinogenic amino acids result in an almost unlimited number of sequential combinations that give proteins their versatility. The sequence of amino acids in a protein is also called the primary structure. From this, locally limited structural motifs such as α-helices and β-sheets are formed, representing the secondary structure. Further intramolecular interactions create the tertiary structure of a protein, which can be seen as the overall three-dimensional structure of the protein. Furthermore, several individual proteins can assemble into a larger complex to form a quaternary structure. There are various methods for investigating the structure of proteins, including nuclear magnetic resonance (NMR) spectroscopy. In NMR spectroscopy, atomic nuclei with a non-zero nuclear spin are polarized by a constant magnetic field and then excited using radio frequency pulses. The emitted resonance frequencies are detected in the form of a free induction decay (FID) and converted into an NMR spectrum by a Fourier transformation. Many NMR experiments are available for researching proteins. By default, a two-dimensional 1H15N-HSQC spectrum is measured, which provides signals for each N-H bond in a protein meaning that one signal is obtained for each N-H in the backbone of the amino acids. Using 3D NMR experiments, these signals can then be assigned to the respective amino acids in the protein sequence. This makes it possible to investigate the dynamics of proteins as well as the formation of complexes with a ligand or another biomacromolecule if they interact. Further 3D NMR experiments also make it possible to assign the side-chains of the protein. With the help of the determined resonance assignments and spatial information from various NOESY spectra, a protein structure can then be calculated using a suitable computer program. Recently, the prediction of protein structures using AI (artificial intelligence)-supported programs has also become more prevalent. In particular, the artificial neural network AlphaFold has been extremely successful in predicting correct structures without any experimental data provided by the user. Chapter 2 of this thesis introduces the research field of small proteins. These are proteins with a length of usually less than 100 amino acids, although definitions in literature vary and upper limits of, for example, 50 or 200 amino acids exist as well. Various other names are also used to describe small proteins, such as μ-proteins or sORF-encoded peptides. The field of small proteins is still relatively new, as they were overlooked in research for many years. One reason for this was the lower limit of 100 codons that was set for the identification of open reading frames (ORFs) in genome projects. This served to exclude numerous biologically irrelevant ORFs from genome annotation. However, this meant that functional ORFs coding for small proteins were also ignored. Another reason was that experimental methods were not designed for the analysis of small proteins, meaning they could often not be detected at all. However, new analytical methods such as ribosome profiling and a generally increased focus on the detection of small proteins have led to their detection in all domains of life. In the research group of Prof. Dr. Schwalbe, small proteins of various prokaryotes were structurally characterized as part of a special priority program by the DFG. NMR spectroscopy was primarily used for this purpose, as it is the method of choice for the investigation of small proteins. The results of this research were published in several articles, two of which are part of this dissertation.

Understanding small molecule binding to RNA can be complicated by an intricate interplay between binding stoichiometry, multiple binding motifs, different occupancies of different binding motifs, and changes in the structure of the RNA under study. Here, we use native top-down mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy to experimentally resolve these factors and gain a better understanding of the interactions between neomycin B and the 40 nt aptamer domain of a neomycin-sensing riboswitch engineered in yeast. Data from collisionally activated dissociation of the 1:1, 1:2 and 1:3 RNA-neomycin B complexes identified a third binding motif C of the riboswitch in addition to the two motifs A and B found in our previous study, and provided occupancies of the different binding motifs for each complex stoichiometry. Binding of a fourth neomycin B molecule was unspecific according to both MS and NMR data. Intriguingly, all major changes in the aptamer structure can be induced by the binding of the first neomycin B molecule regardless of whether it binds to motif A or B as evidenced by stoichiometry-resolved MS data together with titration data from 1H NMR spectroscopy in the imino proton region. Specific binding of the second and third neomycin B molecules further stabilizes the riboswitch aptamer, thereby allowing for a gradual response to increasing concentrations of neomycin B, which likely leads to a fine-tuning of the cellular regulatory mechanism.

Decision letter: Dynamic Na+/H+ exchanger 1 (NHE1) – calmodulin complexes of varying stoichiometry and structure regulate Ca2+-dependent NHE1 activation

When analyzing the Free Induction Decay (FID) signal produced by nuclear magnetic resonance (NMR) spectroscopy, Fourier transforms (FT) are used to decompose time-domain signals arising from nuclear interactions. This transformation enables the extraction of frequency-domain information, allowing for the recognition of patterns within the generated NMR spectra. Most modern NMR processing software applies FT to generate the final spectra. Researchers process FID using various techniques, such as phase correction, windowing, and FT, to enhance the interpretation of the obtained spectra. This processing step requires careful consideration of the characteristics of the original data and can also be influenced by the researchers' experience, often making it time-consuming to produce reliable results. However, recent advancements in artificial intelligence, particularly deep learning, have demonstrated superior pattern recognition capabilities compared to humans in complex scenarios. These developments have been successfully applied to various aspects of NMR spectroscopy. In this study, we demonstrate that neural networks can replace FT in NMR spectroscopy, enabling robust and rapid prediction of spectra and peak lists from FID signals. Our results confirm that deep learning can efficiently process NMR data to generate final spectra. As a proof of concept, we present the resulting spectra, along with peak lists predicted by supplying only FID input to the deep learning algorithm. The generated peak lists can be considered as spectra with infinite resolution.

The Biological Magnetic Resonance Data Bank (BioMagResBank or BMRB), founded in 1988, serves as the archive for data generated by nuclear magnetic resonance (NMR) spectroscopy of biological systems. NMR spectroscopy is unique among biophysical approaches in its ability to provide a broad range of atomic and higher-level information relevant to the structural, dynamic, and chemical properties of biological macromolecules, as well as report on metabolite and natural product concentrations in complex mixtures and their chemical structures. BMRB became a core member of the Worldwide Protein Data Bank (wwPDB) in 2007, and the BMRB archive is now a core archive of the wwPDB. Currently, about 10% of the structures deposited into the PDB archive are based on NMR spectroscopy. BMRB stores experimental and derived data from biomolecular NMR studies. Newer BMRB biopolymer depositions are divided about evenly between those associated with structure determinations (atomic coordinates and supporting information archived in the PDB) and those reporting experimental information on molecular dynamics, conformational transitions, ligand binding, assigned chemical shifts, or other results from NMR spectroscopy. BMRB also provides resources for NMR studies of metabolites and other small molecules that are often macromolecular ligands and/or nonstandard residues. This chapter is directed to the structural biology community rather than the metabolomics and natural products community. Our goal is to describe various BMRB services offered to structural biology researchers and how they can be accessed and utilized. These services can be classified into four main groups: (1) data deposition, (2) data retrieval, (3) data analysis, and (4) services for NMR spectroscopists and software developers. The chapter also describes the NMR-STAR data format used by BMRB and the tools provided to facilitate its use. For programmers, BMRB offers an application programming interface (API) and libraries in the Python and R languages that enable users to develop their own BMRB-based tools for data analysis, visualization, and manipulation of NMR-STAR formatted files. BMRB also provides users with direct access tools through the NMRbox platform.

The analytical potential of nuclear magnetic resonance (NMR) spectroscopy has been recognized since the early days of NMR. It is well known that the NMR signal is linear (proportional to the spin concentration), specific (spin groups have characteristic chemical shifts), and nondestructive (signal recording does not affect the sample). The last aspect is particularly important for biomedical studies, which culminated in NMR imaging (MRI) becoming an indispensable diagnostic tool. The broad application of the quantitative aspect of NMR only started after the development of NMR technology (magnets, electronics, and computers), which, in addition to selectivity, enabled the reproducibility and repeatability of data collection, even in biological systems. In this presentation, quantitative NMR microscopy and NMR spectroscopy will be illustrated by examples from studies of biological systems (live mice, fixed tissue, and body fluids). For instance, it will be shown how NMR spectroscopy can be used to quantify total proteins in biological fluids, irrespective of the protein composition, without the need for method calibration.

Chapter 27. NMR Spectroscopy in Biological Systems