Streptococcus pneumoniae relies on sialic acid uptake for nutrition and human respiratory tract colonisation. The ATP binding cassette (ABC) transporter SatABC-MsmK facilitates this, with SatA being the substrate-binding protein (SBP). We show that SatA specifically recognises the α-anomer of N-acetylneuraminic acid (α-Neu5Ac). Crystallographic analysis, mutagenesis and binding affinity measurements identify conserved residues Phe87, Arg113, Gln216, Arg404 as critical for α-Neu5Ac coordination. Nuclear magnetic resonance spectroscopy confirms selective binding of α-Neu5Ac in buffered solution, despite its low equilibrium abundance. Isothermal titration calorimetry shows high affinity of SatA for the anomeric mixture of Neu5Ac (Kd ≈ 270 nM). The α-anomer preference of SatA, not previously observed in other SBPs, may confer selective advantage to S. pneumoniae by enabling uptake of α-Neu5Ac, the immediate product of sialidase-mediated glycan cleavage. The respiratory pathogen Streptococcus pneumoniae uses the substrate binding protein SatA of the ABC transporter SatBC–MsmK to specifically bind the α-anomer of N-acetylneuraminic acid, the immediate product of sialidase-mediated glycan cleavage.

Sustainable food production systems based on the use of biofertilizers and soil improvers are proposed to mitigate agricultural-related environmental impacts and address the climate crisis. In particular, plant growth-promoting microbes (PGPM) and biochar (Char) have been reported to improve plant growth, soil quality, and crop yield; however, their effects on food quality remain debated. In this study, untargeted metabolomics based on ultra-high performance liquid chromatography-ion mobility-high-resolution mass spectrometry (UHPLC-IMS-HRMS) and proton nuclear magnetic resonance spectroscopy (1H-NMR) are proposed to achieve a comprehensive investigation of the effects of Char, PGPM and Char+PGPM on durum wheat. A total of 88 metabolites were annotated by UHPLC-IMS-HRMS, mainly belonging to carbohydrates, flavones, flavonoids, glycerophospholipids, and glycolipids, while 30 compounds were annotated by 1H-NMR, mostly amino acids and short-chain carboxylic acids. The two datasets were merged with the gluten protein content dataset by using low- and mid-level data fusion approaches, obtaining models that exhibit excellent classification performance. Integrated analysis highlighted that the combined Char+PGPM treatment induced metabolic changes across multiple chemical classes, including enrichment of flavonoids and lipids, and downregulation of carbohydrate metabolites, suggesting a redistribution of carbon resources and modulation of secondary metabolism with potential implications on wheat grain quality.

Eph receptors are involved in the regulation of cell adhesion and migration and are implicated in cancer progression, making them important drug targets. To date, the design of drugs targeting the ligand-binding domain of Eph includes the development of peptide mimetics of the ephrin ligands and the optimization of repurposed drugs. In this work, we report the results of a fragment-based screening (FBS) campaign against the ligand-binding domain of the EphA2 receptor. We introduce the workflow for the selection, filtering and follow-up studies of FBS hits, including an NMR/X-ray hybrid approach for the structure determination of protein/ligand complexes. The proposed workflow allowed us to identify several compounds with the receptor binding affinities of 50-100 µM and IC 50 of 1 µM , better than the activities of the known repurposed drugs. Due to the low molecular weight, the newly developed hits that exhibit an initial biological effect have a high potential for further optimization.

Objective: Reconstituting a membrane protein in a membrane-like environment is an essential factor, determining the relevance of structural data obtained for a membrane protein. Mixtures of lauryl maltose neopentyl glycol (LMNG) with cholesteryl hemisuccinate (CHS) are a recently introduced membrane-like medium with a proven stabilizing effect on membrane proteins of several classes. However, the structure of LMNG/CHS micelles remains underinvestigated. Methods: In the present work, we apply diffusion and nuclear Overhauser effect NMR spectroscopy and the transmembrane domain pf EphA2 as a sensor transmembrane protein to characterize the properties of LMNG/CHS micelles in comparison to other membrane mimetics, including phospholipid bicelles. Results and Discussion: According to the diffusion measurements, CHS addition to LMNG micelles reduces the temperature- and concentration-induced growth of the particles, preventing LMNG from forming non-regular rod-like structures. CHS is evenly distributed within the micelles, with no preference for the protein-adjacent regions. For a model protein, LMNG/CHS provides an environment similar to dodecyl maltoside but distinct from lipid bicelles in terms of lipid-protein contacts. Conclusions: LMNG/CHS is a membrane mimetic that stabilizes membrane proteins, has a defined micellar structure with even CHS distribution, suppresses undesirable rod-like LMNG aggregation, and offers a lipid-protein contact environment different from that of bicelles but similar to dodecyl maltoside.

ABSTRACT A group of researchers from the humanities, economics, social sciences, natural and life science developed a definition of the topics complexity and emergence that can be applied across disciplines. Here, concepts of complexity and emergence in chemistry and biochemistry are discussed, to promote a discourse between the natural and life sciences and philosophy. Although chemical research often employs reductionist strategies, the properties of molecules and their linked functions exhibit emergent properties that cannot be inferred solely from their atomic constituents. Assembly theory and the work of Manfred Eigen offer ways to quantify and predict emergence in chemistry, particularly in relation to the origins and evolution of life. This review emphasizes the chemical prerequisites for life, such as the formation of natural products, the emergence of nucleic acids that carry information, and the functional roles of proteins. From a philosophical standpoint, modern ontology provides a means of understanding reality that is both process‐based and subject‐independent. By integrating chemistry, biology and philosophy, the synopsis of this review addresses the predictive, post facto and historically unique aspects of complex systems, offering a conceptual framework for comprehending the emergence of molecular function and the evolution of living systems.

Guanosine- and deoxyguanosine-rich nucleic acids can form G-quadruplex structures (G4) that are stabilized by guanine tetrads (G4 tetrads). G4s find numerous applications in biotechnology. Here, we study a so called thrombin-binding aptamer (TBA), developed by SELEX procedures, that adopts a G4 conformation and inhibits clotting of thrombin. We investigate the TBA G4 and its variants with either four adenosine desoxynucleotides or four abasic sites attached either to the 5 '-terminus (A4-TBA and ab4-TBA) or the 3 '-terminus (TBA-ab4 and TBA-A4). These variants have been shown to exhibit differential anticlotting activities previously. The variant TBA-ab4, which was the most biological active in earlier investigations, has an exceptional stability against nuclease restriction, while all other variants show similar decay rates in mammalian serum. Biophysical characterization of the variants reveals that the structure of the aptamer remains unchanged, but that also their different thermal stabilities correlate with the anticlotting activity of TBA. Hydrogen exchange quantified by nuclear magnetic resonance spectroscopy (NMR) reveals individual G4 tetrad thermodynamics. Our data indicate that while enthalpy, entropy and free energy of base pair opening show surprisingly low variation, a hotspot for stabilization of the G4 is present at the 3 ', 5 ' terminal tetrad of TBA.

Fragment-based drug discovery (FBDD) is an effective approach for exploring chemical space using small, low-affinity fragments as starting points to facilitate development of lead compounds. Strategies to improve fragment potency include fragment merging and linking to generate higher-affinity inhibitors. Recently, artificial intelligence (AI) and machine learning (ML) have accelerated this process through structure-based optimization and generative compound design. Here, we present an AI-assisted FBDD workflow applied to the SARS-CoV-2 macrodomain (Mac1), a conserved viral protein involved in immune evasion and ADP-ribose metabolism. Using available structural data and previously identified fragments, we combined deep learning with molecular docking to design novel Mac1 binders. Selected compounds were synthesized and validated by NMR spectroscopy and X-ray crystallography, demonstrating improved binding relative to the original fragment hits with KD values in the range of 299-990 µM. This study demonstrates the advantages of integrating AI with FBDD to streamline molecular design, providing a data-driven framework for discovering new Mac1 inhibitors and guiding future antiviral drug development.

While the GNRA tetraloops are an extensively studied and common RNA motif, their dynamic NMR structures in solution integrating state-of-the-art NMR parameters such as residual dipolar couplings (RDC) and cross correlated relaxation rates (CCR) have previously not been determined. Given their dominant occurrence among tetraloops in the PDB and the advance of experimentally reweighted MD simulations, the present work aims at investigating the entire conformational space of two known tetraloop sequences by an extensive NMR investigation of NOEs, J -couplings constants, RDCs and CCRs. As classical structure calculation proved insufficient for the more dynamic tetraloop, we turned to Bayesian/maximum entropy reweighting of molecular simulations using our rich set of experiments. The resulting ensembles were clustered and compared to classically restrained structure calculations, structures from the PDB and models predicted by the prediction algorithms Farfar and AlphaFold 3. Our results show that GNRA-like tetraloops can vary in dynamic sampling of conformational space. They highlight the importance of individual experimental validation of computationally obtained dynamic ensembles and model predictions.

Long noncoding RNAs (lncRNAs) play key roles in gene regulation. One potential regulation mechanism involves the formation of RNA•DNA:DNA triplexes. In these triplexes, the lncRNA binds in the major groove of a target DNA via Hoogsteen base pair formation. Here, we investigated the impact of the underlying RNA binding on the stability of the DNA duplex target to gain insights into the triplex stability at base pair resolution with an isolated triplex system. Quantification of the temperature-dependent exchange of imino hydrogen atoms with solvent of the target DNA duplex allows determination of the changes in the stability of individual DNA duplex base pairs upon triplex formation. The data shown here investigates an antiparallel triplex, formed between the lncRNA hypoxia-inducible factor 1-α antisense RNA 1 (HIF1α-AS1) and the DNA target adrenomedullin (ADM), important in cardiovascular diseases. Triplex formation alters DNA structure and stability by affecting both hydrogen bonding strength and nucleobase-stacking interactions. These thermodynamic insights support bioinformatic methods to predict triplex stability and enhance our understanding of RNA•DNA:DNA triplex formation.

Isotopic enrichment of pharmacologically relevant protein targets is crucial for structural studies by nuclear magnetic resonance (NMR) and plays a key role in advancing structure-guided drug discovery. Many clinically important drug targets require expression in eukaryotic systems-such as mammalian, yeast, or insect cells-rather than prokaryotic hosts. This requirement limits the feasibility of high-throughput isotopic labeling and poses challenges for obtaining uniformly isotope-labeled proteins suitable for NMR analysis. While several enrichment strategies have been developed, no broadly applicable enrichment platform has emerged for eukaryotic expression systems. In this study, we introduce Cupriavidus necator as an alternative biological source for 15N and 13C isotopic enrichment to support protein production in eukaryotic systems. To evaluate this approach, we selected the kinase domain of EPHA2, a receptor tyrosine kinase implicated in colorectal cancer progression and an important target for therapeutic inhibitor development. Isotopic incorporation was quantified using liquid chromatography-mass spectrometry (LC-MS), revealing enrichment levels of 79% for 15N and 69% for 13C. These results demonstrate that Cupriavidus necator can serve as a robust and flexible platform for generating isotopically enriched biomolecules compatible with eukaryotic protein expression, thereby enabling NMR investigations of disease-relevant protein targets.

Targeting RNA is a rich, yet largely untackled opportunity for controlling biological functions, with high potential for therapeutic intervention. However, it remains inherently challenging. Beyond RNA structural diversity, functional RNA motifs are frequently context-dependent and transient, complicating the rational design of selective small-molecule binders. We here develop novel photoswitchable ligands to target RNA. They offer highly desirable, precise intervention by enabling light-controlled regulation of both direct RNA interactions and downstream events. Unfortunately, access to such photoswitchable RNA molecular tools is scarce, requiring complex and lengthy synthesis routes. We present a readily adaptable platform for the straightforward synthesis of photoswitchable RNA binders capable of targeting pre-mRNA and restoring functional survival motor neuron (SMN) protein levels by rescuing exon inclusion. Evaluation of our compounds demonstrated that both fluorination and heteroaryl groups (e.g., benzo- and thioxozaole) enhance binding affinity to the targeted dsRNA with in-cellulo activity. Importantly, molecular recognition and structure-activity relationships were rationalized through a combination of computational studies and NMR spectroscopy.

Dysregulated mitochondrial Ca2+ influx is a unifying driver of neurodegeneration, compromising neuronal bioenergetics and survival. In Parkinson’s disease (PD), impaired mitochondrial Ca2+ uptake is a decisive trigger for dopaminergic (DA) neuron loss, yet the molecular identity of the responsible channel has remained unresolved. Although the mitochondrial Ca2+ uniporter (MCU) is regarded as the principal conduit, global MCU ablation is non-lethal and MCU-deficient neurons retain basal Ca2+ uptake, pointing to the existence of a vital alternative pathway. Here we identify prohibitin2 (PHB2) forms this long-sought MCU-independent Ca2+ channel. Conditional ablation of PHB2 in DA neurons of mice induces hallmark PD pathology, including >70% substantia nigra neuron loss and severe motor deficits. By integrating live-cell mitochondrial Ca2+ imaging, mitoplast patch-clamp, single-molecule photometry, and high-field solution NMR, we demonstrate that PHB2 oligomerizes into a hexameric Ca2+ channel (~30 Å lumen). Structure-guided mutagenesis of four pore-lining residues abolished Ca2+ conductance, and this disruption of PHB2 channel function in DA neurons drives degeneration. Crucially, rescue experiments by adeno-associated virus mediated re-expression of wild-type PHB2, but not channel-dead mutant, in PHB2-DA-knockout mice restores >80% of DA neurons and reverses motor deficits. These findings identify PHB2 as the essential mitochondrial Ca2+ channel sustaining dopaminergic survival and nigral integrity, resolve a central enigma in mitochondrial biology, and establish the PHB2 pore as a tractable therapeutic target in PD. More broadly, modulation of PHB2 channel activity may represent a general strategy to reinforce mitochondrial resilience across neurodegenerative diseases.

Several SARS-CoV-2 variants have evolved with clinical relevance due to their structural and functional impact on viral proteins and genomic RNA structures. A comprehensive structural and functional characterization of single-nucleotide variations in the 5 '-untranslated region (UTR) of SARS-CoV-2 has remained elusive. The co-evolution of 5 '-UTR stem-loop 1 (SL1) and non-structural protein (nsp) 1 mutants are of particular importance, as both are key in directing the translation of the viral genome. Here, we investigate the structure and function of the most frequently emerging mutations in SL1 and nsp1. Mutation C21U in the apical loop of SL1 shows changed loop dynamics and reduced escape from repression by nsp1 mutants. Mutation analyses of the pyrimidine loop and the apical helix of SL1 identify preferred sequence motifs for escape from nsp1 repression. Importantly, sequence preferences are governed by the structural features, with suboptimal pyrimidine sequences escaping repression when presented in the SL1 context. Compared to the nsp1 wild type (wt), the currently circulating nsp1 linker variant S135R is much more sensitive toward sequence and structure variations of the apical loop of SL1. Thus, our study provides new insights into the structure-function relationship and co-evolution between viral RNA structures and viral proteins.

Targeting structured RNA elements with small molecules has emerged as a promising yet technically challenging strategy for antiviral drug discovery. Here, we present a comprehensive and experimentally validated workflow for the integrative in silico and in vitro screening of RNA-binding small molecules. The approach is exemplified using conserved RNA elements from the SARS-CoV-2 genome, including the 5'-terminal stem-loop 1 and the programmed -1 ribosomal frameshift pseudoknot, but is broadly applicable to other structured RNAs. The workflow integrates high-resolution RNA structural ensemble generation with virtual screening (VS) and nuclear magnetic resonance (NMR)-based experimental validation. Conformational ensembles generated by fragment-assembly approaches serve as targets for docking chemically diverse fragments and lead-like libraries. Top-ranked compounds are prioritized through consensus scoring and evaluated using ligand- and RNA-observed NMR experiments to confirm binding, characterize interaction modes, and assess specificity. Such ranking allows for NMR-guided fragment optimization, which enables systematic improvement of solubility, affinity, and selectivity through iterative medicinal chemistry in the pharmaceutical pipeline. Detailed procedures are provided for library preparation, ensemble-based VS, hit validation, data interpretation, and progression toward functional assays, together with practical considerations, quality-control parameters, and troubleshooting guidance to ensure reproducibility. By combining computational and experimental strategies that select for high-specificity ligands within a unified framework, this set of protocols accelerates the discovery and optimization of RNA-targeting small molecules and provides a scalable platform for RNA-focused drug discovery. © 2026 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Target and library preparation for virtual screening Basic Protocol 2: Ensemble-based virtual screening of low-molecular-weight compounds against RNA targets Basic Protocol 3: Comparative hit prioritization and selectivity filtering for RNA-binding small molecules Basic Protocol 4: Preparation of RNA samples for in vitro validation of small-molecule binding Basic Protocol 5: NMR-based in vitro screening of RNA-small molecule interactions Support Protocol: Preparation of ligand stocks and NMR-based quality control Basic Protocol 6: Characterization and prioritization of validated RNA-binding hits.

In this Voices article, participants from the recent wwPDB Workshop on Fragment Screening at the EMBL-EBI and their colleagues discuss recent advances, current challenges, and future opportunities in crystallographic and NMR fragment screening and describe how the PDB is adapting to support this rapidly evolving field.

Acute myeloid leukemia (AML) cells exhibit pronounced metabolic plasticity, yet how amino acid supply is coordinated to sustain leukemic metabolism remains poorly understood. Here, we show that AML cells catabolize extracellular proteins as a major source of amino acids through lysosomal degradation of albumin. This proteocatabolic activity supports anabolic processes and mitochondrial energy production and establishes a regulated, high-throughput regime of primary nitrogen-containing metabolites (nitrogen regimen). Sustained proteocatabolism inevitably generates ammonia, and we find elevated ammonia concentrations in bone marrow plasma from newly diagnosed AML patients that decline with effective induction therapy. Using metabolomics, isotope tracing and targeted genetic and pharmacological manipulations, we identify glutamate-ammonia ligase (GS/GLUL) as a central enzyme that buffers proteocatabolism-derived ammonia by stabilizing intracellular nitrogen homeostasis. Loss of GS function limits sustainable nitrogen handling capacity, thereby impairing leukemic proliferation and delaying disease progression in vivo. Together, our findings define extracellular protein catabolism as a regulating nitrogen management strategy in AML and reveal GS as a capacity-defining vulnerability of proteocatabolic growth.

Quantitative information on protein abundance is crucial to understand biological processes and is therefore frequently gathered in proteomic studies. However, the quality of a quantitative proteomic dataset is greatly affected by the number of missing values, which need to be minimized to produce robust and meaningful data. In this context, small proteins (≤100 amino acids) pose specific analytical challenges, which hinder their efficient identification and quantitative characterization in complex proteomes. In this study, methods for sample preparation and MS-data processing are systematically evaluated for their contribution to identification and quantification of small proteins of Clostridioides difficile 630 Δerm. Results show that small protein enrichment can enhance the number of identified and quantified proteins also for low abundant small proteins. Through application of spectral libraries for identification of MS spectra the number of robustly quantified proteins is increased and a lower limit of their detection is reached. Additionally, the dataset presented here is currently the most comprehensive protein repository for C. difficile covering 84.7% of the predicted proteome and 61.4% of all predicted small proteins of this important pathogen.

Correction for ‘ In situ formation of transcriptional modulators using non-canonical DNA i-motifs’ by Puja Saha et al. , Chem. Sci. , 2020, 11 , 2058–2067, https://doi.org/10.1039/D0SC00514B.

A major challenge in electron cryo‐microscopy (ECM) imaging is preparing the protein specimen without the artifacts caused by the surface tension at the air‐water interface (AWI). Here, we report nanosecond hyperquenching (NHQ) – a method of preparing ECM samples without AWI‐bound protein macromolecules. The fast narrow sample jet impinges the eutectic propane‐ethane (PET) liquid cryogen at 77 K and breaks up, forming 30–150‐nm‐thick vitrified films. NHQ films with the protein particles are formed directly in the PET cryogen, precluding AWI tension‐driven protein adsorption, preferred orientation, subunit dissociation and denaturation. The formed film surfaces are essentially specimen‐free, with a 2.7‐nm‐thick protein depleted layer of hyperquenched glassy water (HGW). This “surface sealing” appears to be the first essential stage of vitrification at NHQ conditions; it occurs in about 35 ps on cryogen encounter. We outline the depletion mechanism, where the growing HGW layer displaces protein particles from the surface inwards the film.

An approach combining virtual and nuclear magnetic resonance (NMR)-based screening is presented here to identify low molecular weight molecules (small molecules) targeting viral RNA elements from the SARS-CoV-2 genome. The so-called high-resolution RNA structural Fragment Assembly of RNA with Full-Atom Refinement 2 (FARFAR2) ensembles of the conserved 5'-terminal stem-loop 1 (SL1) and the pseudoknot of the -1 programed frameshift element are used as targets for binding of small molecules of three different virtual libraries of compounds. The resulting hits predicted by virtual screening are probed for their binding to the two RNA elements by ligand- and target-based NMR experiments. The results demonstrate that the integration of virtual and experimental NMR screening efficiently identifies RNA-binding small molecules as start molecular entities to advance RNA-targeted antiviral therapies in an efficient manner. The strategy does not only apply to SARS-CoV-2, but also provides a rapid, highly specific route to discovering therapeutics for other RNA-based pathogens, highlighting the critical role of RNA structural data in enriching virtual drug discovery efforts.