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Accurate extraction of multiplet parameters, such as J-couplings and chemical shifts, play a vital role in small molecule analysis using nuclear magnetic resonance (NMR) spectroscopy. These parameters provide essential quantitative information about molecular structures, interatomic interactions, and chemical environments, enabling precise characterization of small organic compounds. This poster presents an innovative omputational approach that utilizes state-of-the-art deep learning techniques, specifically detection transformers, to automate and optimize the extraction of multiplet parameters from 1D NMR spectra of small molecules. By incorporating these advanced computational methods, experimenters can achieve improved efficiency, accuracy, and speed in analyzing and characterizing small organic compounds using NMR spectroscopy.

RNA, widely recognized as an information-carrier molecule, is capable of catalyzing essential biological processes through ribozymes. Despite their ubiquity, specific functions in a biological context and phenotypes based on the ribozymes' activity are often unknown. Here, we present the discovery of a subgroup of minimal HDV-like ribozymes, which reside 3' to viral tRNAs and appear to cleave the 3'-trailers of viral premature tRNA transcripts. This proposed tRNA-processing function is unprecedented for any ribozymes, thus, we designate this subgroup as theta ribozymes. Most theta ribozymes were identified in Caudoviricetes bacteriophages, the main constituent (>90%) of the mammalian gut virome. Intriguingly, our findings further suggest the involvement of theta ribozymes in the transition of certain bacteriophages between distinct genetic codes, thus possibly contributing to the phage lysis trigger. Our discovery expands the limited repertoire of biological functions attributed to HDV-like ribozymes and provides insights into the fascinating world of RNA catalysis.

Trillions of microorganisms, collectively known as the microbiome, inhabit our bodies with the gut microbiome being of particular interest in biomedical research. Bacteriophages, the dominant virome constituents, can utilize suppressor tRNAs to switch to alternative genetic codes (e.g., the UAG stop-codon is reassigned to glutamine) while infecting hosts with the standard bacterial code. However, what triggers this switch and how the bacteriophage manipulates its host is poorly understood. Here, we report the discovery of a subgroup of minimal hepatitis delta virus (HDV)-like ribozymes - theta ribozymes - potentially involved in the code switch leading to the expression of recoded lysis and structural phage genes. We demonstrate their HDV-like self-scission behavior in vitro and find them in an unreported context often located with their cleavage site adjacent to tRNAs, indicating a role in viral tRNA maturation and/or regulation. Every fifth associated tRNA is a suppressor tRNA, further strengthening our hypothesis. The vast abundance of tRNA-associated theta ribozymes - we provide 1753 unique examples - highlights the importance of small ribozymes as an alternative to large enzymes that usually process tRNA 3'-ends. Our discovery expands the short list of biological functions of small HDV-like ribozymes and introduces a previously unknown player likely involved in the code switch of certain recoded gut bacteriophages.

Holliday 4-way junctions are key to important biological DNA processes (insertion, recombination, and repair) and are dynamic structures that adopt either open or closed conformations, the open conformation being the biologically active form. Tetracationic metallo-supramolecular pillarplexes display aryl faces about a cylindrical core, an ideal structure to interact with open DNA junction cavities. Combining experimental studies and MD simulations, we show that an Au pillarplex can bind DNA 4-way (Holliday) junctions in their open form, a binding mode not accessed by synthetic agents before. Pillarplexes can bind 3-way junctions too, but their large size leads them to open up and expand that junction, disrupting the base pairing, which manifests in an increased hydrodynamic size and lower junction thermal stability. At high loading, they rearrange both 4-way and 3-way junctions into Y-shaped forks to increase the available junction-like binding sites. Isostructural Ag pillarplexes show similar DNA junction binding behavior but lower solution stability. This pillarplex binding contrasts with (but complements) that of metallo-supramolecular cylinders, which prefer 3-way junctions and can rearrange 4-way junctions into 3-way junction structures. The pillarplexes' ability to bind open 4-way junctions creates exciting possibilities to modulate and switch such structures in biology, as well as in synthetic nucleic acid nanostructures. In human cells, the pillarplexes do reach the nucleus, with antiproliferative activity at levels similar to those of cisplatin. The findings provide a new roadmap for targeting higher-order junction structures using a metallo-supramolecular approach, as well as expanding the toolbox available to design bioactive junction binders into organometallic chemistry.

We introduce a deep learning-based deconvolution approach for 1H NMR spectra, developed by leveraging concepts from the field of physics informed-learning, intelligent labeling, and tailored high dynamic range (HDR) spectral preprocessing. Since automation and faster workflows are major concerns in NMR spectroscopy, the algorithm handles uncorrected spectra without strict assumptions on phase and baseline correction as well as line shape. Due to the lack of high quality and consistently labeled experimental spectra in quantities needed to train modern deep learning models, we relied on synthetic spectra creation. Moreover, instead of training with synthetic spectra consisting of single lines, we created synthetic multiples that further supported a realistic deconvolution. We achieved super-human performance on corrected and uncorrected synthetic spectra. Finally, and most importantly, the results on synthetic data translate well to experimental spectra despite the covariate shift. Thus, this tool is a promising candidate for automated expert-level deconvolution of experimental HDR 1H NMR spectra.

Riboswitches are structural elements of mRNA involved in the regulation of gene expression by responding to specific cellular metabolites. To fulfil their regulatory function, riboswitches prefold into an active state, the so-called binding competent form, that guarantees metabolite binding and allows a consecutive refolding of the RNA. Here, we describe the folding pathway to the binding competent form as well as the ligand free structure of the moaA riboswitch of E. coli. This RNA proposedly responds to the molybdenum cofactor (Moco), a highly oxygen-sensitive metabolite, essential in the carbon and sulfur cycles of eukaryotes. K+- and Mg2+-dependent footprinting assays and spectroscopic investigations show a high degree of structure formation of this RNA already at very low ion-concentrations. Mg2+ facilitates additionally a general compaction of the riboswitch towards its proposed active structure. We show that this fold agrees with the earlier suggested secondary structure which included also a long-range tetraloop/tetraloop-receptor like interaction. Metal ion cleavage assays revealed specific Mg2+-binding pockets within the moaA riboswitch. These Mg2+ binding pockets are good indicators for the potential Moco binding site, since in riboswitches, Mg2+ was shown to be necessary to bind phosphate-carrying metabolites. The importance of the phosphate and of other functional groups of Moco is highlighted by binding assays with tetrahydrobiopterin, the reduced and oxygen-sensitive core moiety of Moco. We demonstrate that the general molecular shape of pterin by its own is insufficient for the recognition by the riboswitch.

Single-molecule microscopy is often used to observe and characterize the conformational dynamics of nucleic acids (NA). Due to the large variety of NA structures and the challenges specific to single-molecule observation techniques, the data recorded in such experiments must be processed via multiple statistical treatments to finally yield a reliable mechanistic view of the NA dynamics. In this chapter, we propose a comprehensive protocol to analyze single-molecule trajectories in the scope of single-molecule Förster resonance energy transfer (FRET) microscopy. The suggested protocol yields the conformational states common to all molecules in the investigated sample, together with the associated conformational transition kinetics. The given model resolves states that are indistinguishable by their observed FRET signals and is estimated with 95% confidence using error calculations on FRET states and transition rate constants. In the end, a step-by-step user guide is given to reproduce the protocol with the Multifunctional Analysis Software to Handle single-molecule FRET data (MASH-FRET).

Fast and efficient site-specific labeling of long RNAs is one of the main bottlenecks limiting distance measurements by means of Förster resonance energy transfer (FRET) or electron paramagnetic resonance (EPR) spectroscopy. Here, we present an optimized protocol for dual end-labeling with different fluorophores at the same time meeting the restrictions of highly labile and degradation-sensitive RNAs. We describe in detail the dual-labeling of a catalytically active wild-type group II intron as a typical representative of long functional RNAs. The modular procedure chemically activates the 5′-phosphate and the 3′-ribose for bioconjugation with a pair of fluorophores, as shown herein, or with spin labels. The mild reaction conditions preserve the structural and functional integrity of the biomacromolecule and results in covalent, dual-labeled RNA in its pre-catalytic state in yields suitable for both ensemble and single-molecule FRET experiments.

This chapter focuses on the interaction of metal ions mainly with RNA. It is an update of the previous Chapter 3.21 in the 2nd Edition of Comprehensive Inorganic Chemistry II (2013) but focusing solely on RNA. Metal ions are key to folding, structure, and function of any nucleic acid. These interactions are generally of a weak and highly dynamic nature as they concern mostly K+ and Mg2+ in living organisms. Aside from the large excess of loosely bound ions for charge compensation, a network of inner-sphere and outer-sphere interactions holds more specifically bound ions in place. Hence, metal ion binding to larger RNAs is rather complicated and has many facets. After a few general considerations on the basic properties of metal ions and the potential coordination sites on the RNA, the thermodynamics of metal ion binding to RNA and known metal ion binding motifs in RNA are described. This is followed by today's knowledge on the role of metal ions in folding, dynamics, sensing, and/or catalysis of riboswitches and ribozymes, respectively, is summarized.

Single-molecule FRET (smFRET) is a versatile technique to study the dynamics and function of biomolecules since it makes nanoscale movements detectable as fluorescence signals. The powerful ability to infer quantitative kinetic information from smFRET data is, however, complicated by experimental limitations. Diverse analysis tools have been developed to overcome these hurdles but a systematic comparison is lacking. Here, we report the results of a blind benchmark study assessing eleven analysis tools used to infer kinetic rate constants from smFRET trajectories. We test them against simulated and experimental data containing the most prominent difficulties encountered in analyzing smFRET experiments: different noise levels, varied model complexity, non-equilibrium dynamics, and kinetic heterogeneity. Our results highlight the current strengths and limitations in inferring kinetic information from smFRET trajectories. In addition, we formulate concrete recommendations and identify key targets for future developments, aimed to advance our understanding of biomolecular dynamics through quantitative experiment-derived models.

Single-molecule FRET (smFRET) is a versatile technique to study the dynamics and function of biomolecules since it makes nanoscale movements detectable as fluorescence signals. The powerful ability to infer quantitative kinetic information from smFRET data is, however, complicated by experimental limitations. Diverse analysis tools have been developed to overcome these hurdles but a systematic comparison is lacking. Here, we report the results of a blind benchmark study assessing eleven analysis tools used to infer kinetic rate constants from smFRET trajectories. We test them against simulated and experimental data containing the most prominent difficulties encountered in analyzing smFRET experiments: different noise levels, varied model complexity, non-equilibrium dynamics, and kinetic heterogeneity. Our results highlight the current strengths and limitations in inferring kinetic information from smFRET trajectories. In addition, we formulate concrete recommendations and identify key targets for future developments, aimed to advance our understanding of biomolecular dynamics through quantitative experiment-derived models.

Quantitative interpretation of single-molecule FRET experiments requires a model of the dye dynamics to link experimental energy transfer efficiencies to distances between atom positions. We have developed FRETraj, a Python module to predict FRET distributions based on accessible-contact volumes (ACV) and simulated photon statistics. FRETraj helps to identify optimal fluorophore positions on a biomolecule of interest by rapidly evaluating donor-acceptor distances. FRETraj is scalable and fully integrated into PyMOL and the Jupyter ecosystem. Here, we describe the conformational dynamics of a DNA hairpin by computing multiple ACVs along a molecular dynamics trajectory and compare the predicted FRET distribution with single-molecule experiments. FRET-assisted modeling will accelerate the analysis of structural ensembles in particular dynamic, non-coding RNAs and transient protein-nucleic acid complexes.

The fidelity of group II intron self-splicing and retrohoming relies on long-range tertiary interactions between the intron and its flanking exons. By single-molecule FRET, we explore the binding kinetics of the most important, structurally conserved contact, the exon and intron binding site 1 (EBS1/IBS1). A comparison of RNA-RNA and RNA-DNA hybrid contacts identifies transient metal ion binding as a major source of kinetic heterogeneity which typically appears in the form of degenerate FRET states. Molecular dynamics simulations suggest a structural link between heterogeneity and the sugar conformation at the exon-intron binding interface. While Mg2+ ions lock the exon in place and give rise to long dwell times in the exon bound FRET state, sugar puckering alleviates this structural rigidity and likely promotes exon release. The interplay of sugar puckering and metal ion coordination may be an important mechanism to balance binding affinities of RNA and DNA interactions in general.

Imaging fluorescently labeled biomolecules on a single-molecule level is a well-established technique to follow intra- and intermolecular processes in time, usually hidden in the ensemble average. The classical approach comprises surface immobilization of the molecule of interest, which increases the risk of restricting the natural behavior due to surface interactions. Encapsulation of such biomolecules into surface-tethered phospholipid vesicles enables to follow one molecule at a time, freely diffusing and without disturbing surface interactions. Further, the encapsulation allows to keep reaction partners (reactants and products) in close proximity and enables higher temperatures otherwise leading to desorption of the direct immobilized biomolecules. Here, we describe a detailed protocol for the encapsulation of a catalytically active RNA starting from surface passivation over RNA encapsulation to data evaluation of single-molecule FRET experiments in TIRF microscopy. We present an optimized procedure that preserves RNA functionality and applies to investigations of, e.g., large ribozymes and RNAs, where direct immobilization is structurally not possible.

Labeling of large RNAs with reporting entities, e.g., fluorophores, has significant impact on RNA studies in vitro and in vivo. Here, we describe a minimally invasive RNA labeling method featuring nucleotide and position selectivity, which solves the long-standing challenge of how to achieve accurate site-specific labeling of large RNAs with a least possible influence on folding and/or function. We use a custom-designed reactive DNA strand to hybridize to the RNA and transfer the alkyne group onto the targeted adenine or cytosine. Simultaneously, the 3′-terminus of RNA is converted to a dialdehyde moiety under the experimental condition applied. The incorporated functionalities at the internal and the 3′-terminal sites can then be conjugated with reporting entities via bioorthogonal chemistry. This method is particularly valuable for, but not limited to, single-molecule fluorescence applications. We demonstrate the method on an RNA construct of 275 nucleotides, the btuB riboswitch of Escherichia coli.

Metal-mediated base pairs expand the repertoire of nucleic acid structures and dynamics. Here we report solution structures and dynamics of duplex DNA containing two all-natural C-HgII-T metallo base pairs separated by six canonical base pairs. NMR experiments reveal a 3:1 ratio of well-resolved structures in dynamic equilibrium. The major species contains two (N3)T-HgII-(N3)C base pairs in a predominantly B-form helix. The minor species contains (N3)T-HgII-(N4)C base pairs and greater A-form characteristics. Ten-fold different 1J coupling constants (15N,199Hg) are observed for (N3)C-HgII (114 Hz) versus (N4)C-HgII (1052 Hz) connectivities, reflecting differences in cytosine ionization and metal-bonding strengths. Dynamic interconversion between the two types of C-HgII-T base pairs are coupled to a global conformational exchange between the helices. These observations inspired the design of a repetitive DNA sequence capable of undergoing a global B-to-A-form helical transition upon adding HgII, demonstrating that C-HgII-T has unique switching potential in DNA-based materials and devices.

Exploring the spatiotemporal dynamics of biomolecules on a single-molecule level requires innovative ways to make them spectroscopically visible. Fluorescence resonance energy transfer (FRET) uses a pair of organic dyes as reporters to measure distances along a predefined biomolecular reaction coordinate. For this nanoscopic ruler to work, the fluorescent labels need to be coupled onto the molecule of interest in a bioorthogonal and site-selective manner. Tagging large non-coding RNAs with single-nucleotide precision is an open challenge. Here we summarize current strategies in labeling riboswitches and ribozymes for fluorescence spectroscopy and FRET in particular. A special focus lies on our recently developed, DNA-guided approach that inserts two fluorophores through a stepwise process of templated functionality transfer and click chemistry.

Life depends on metals. While carbon, in terms of abundance and versatility, is considered THE element of life, the vast variety and diversity of the chemistry taking place in living organisms could not be achieved without metal ions. More than twenty metals are found in the human body, most of them being essential, some beneficial, and for others it is still unknown what role they might fulfil in a living cell. Here we give a short introduction into the bioinorganic world of the periodic table, providing just a few examples of key metals for life and aiming to give a flavour to gain further insights into this exciting field of inorganic chemistry at the intersection to the life sciences.

Tc-DNA is a conformationally constrained oligonucleotide analogue which shows significant increase in thermal stability when hybridized with RNA, DNA or tc-DNA. Remarkably, recent studies revealed that tc-DNA antisense oligonucleotides (AO) hold great promise for the treatment of Duchenne muscular dystrophy and spinal muscular atrophy. To date, no high-resolution structural data is available for fully modified tc-DNA duplexes and little is known about the origins of their enhanced thermal stability. Here, we report the structures of a fully modified tc-DNA oligonucleotide paired with either complementary RNA, DNA or tc-DNA. All three investigated duplexes maintain a right-handed helical structure with Watson-Crick base pairing and overall geometry intermediate between A- and B-type, but closer to A-type structures. All sugars of the tc-DNA and RNA residues adopt a North conformation whereas the DNA deoxyribose are found in a South-East-North conformation equilibrium. The conformation of the tc-DNA strand in the three determined structures is nearly identical and despite the different nature and local geometry of the complementary strand, the overall structures of the examined duplexes are very similar suggesting that the tc-DNA strand dominates the duplex structure.

Single-molecule microscopy has become a widely used technique in (bio)physics and (bio)chemistry. A popular implementation is single-molecule Förster Resonance Energy Transfer (smFRET), for which total internal reflection fluorescence microscopy is frequently combined with camera-based detection of surface-immobilized molecules. Camera-based smFRET experiments generate large and complex datasets and several methods for video processing and analysis have been reported. As these algorithms often address similar aspects in video analysis, there is a growing need for standardized comparison. Here, we present a Matlab-based software (MASH-FRET) that allows for the simulation of camera-based smFRET videos, yielding standardized data sets suitable for benchmarking video processing algorithms. The software permits to vary parameters that are relevant in cameras-based smFRET, such as video quality, and the properties of the system under study. Experimental noise is modeled taking into account photon statistics and camera noise. Finally, we survey how video test sets should be designed to evaluate currently available data analysis strategies in camera-based sm fluorescence experiments. We complement our study by pre-optimizing and evaluating spot detection algorithms using our simulated video test sets.

Labeling of long RNA molecules in a site-specific yet generally applicable manner is integral to many spectroscopic applications. Here we present a novel covalent labeling approach that is site-specific and scalable to long intricately folded RNAs. In this approach, a custom-designed DNA strand that hybridizes to the RNA guides a reactive group to target a preselected adenine residue. The functionalized nucleotide along with the concomitantly oxidized 3'-terminus can subsequently be conjugated to two different fluorophores via bio-orthogonal chemistry. We validate this modular labeling platform using a regulatory RNA of 275 nucleotides, the btuB riboswitch of Escherichia coli, demonstrate its general applicability by modifying a base within a duplex, and show its site-selectivity in targeting a pair of adjacent adenines. Native folding and function of the RNA is confirmed on the single-molecule level by using FRET as a sensor to visualize and characterize the conformational equilibrium of the riboswitch upon binding of its cofactor adenosylcobalamin. The presented labeling strategy overcomes size and site constraints that have hampered routine production of labeled RNA that are beyond 200 nt in length.

Although lead(II) is naturally not associated with nucleic acids, this metal ions has been applied with DNA and RNA in various contexts. Pb2+ is an excellent hydrolytic metal ion for nucleic acids, which is why it is mainly used as probing agent for secondary structure and to determine metal ion binding sites both in vitro and in vivo. A further application of lead(II) is in structural studies, i.e., NMR, but also in X-ray crystallography, mostly using this heavy metal to solve the phase problem in the latter method. The structures of tRNAPhe, RNase P, HIV-1 DIS, and the leadzyme are discussed here in detail. A major part of this review is devoted to the cleavage properties of lead(II) with RNA because of its excellence in catalyzing phosphodiester cleavage. Metal ion binding sites in large naturally occurring ribozymes are regularly determined by Pb2+ cleavage, and also in the in vitro selected socalled leadzyme, this metal ion is the decisive key to backbone cleavage at a specific site. Lead(II) was used in the first in vitro selection that yielded a catalytic DNA, i.e., the DNAzyme named GR5. Next to the GR5, the so-called 8-17E is the second most prominent DNAzyme today. Derivatives of these two lead(II)-dependent DNAzymes, as well as the G-quadruplex forming PS2.M have been applied to detect lead(II) in the lower nanomolar range not only in the test tube but also in body fluids. Due to the toxicity of lead(II) for living beings, this is a highly active research field. Finally, further applications of lead(II)-dependent DNAzymes, e.g., in the construction of nanocomputers, are also discussed.