Bioinspired Fluorine Labeling for 19F NMR-Based Plasma Amine Profiling

Metabolite profiling serves as a powerful tool that advances our understanding of biological systems, disease mechanisms, and environmental interactions. In this study, we present an approach employing 19F-nuclear magnetic resonance (19F NMR) spectroscopy for plasma amine profiling. This method utilizes a highly efficient and reliable fluorine-labeling reagent, 3,5-difluorosalicylaldehyde, which effectively emulates pyridoxal phosphate, facilitating the formation of Schiff base compounds with primary amines. The fluorine labeling allows for distinct resolution of 19F NMR signals from amine mixtures, leading to precise identification and quantification of amine metabolites in human plasma. This advancement offers valuable tools for furthering metabolomics research.

Effects of Processing-Induced Contamination on Organic Electronic Devices

Organic semiconductors are a family of pi-conjugated compounds used in many applications, such as displays, bioelectronics, and thermoelectrics. However, their susceptibility to processing-induced contamination is not well understood. Here, it is shown that many organic electronic devices reported so far may have been unintentionally contaminated, thus affecting their performance, water uptake, and thin film properties. Nuclear magnetic resonance spectroscopy is used to detect and quantify contaminants originating from the glovebox atmosphere and common laboratory consumables used during device fabrication. Importantly, this in-depth understanding of the sources of contamination allows the establishment of clean fabrication protocols, and the fabrication of organic field effect transistors (OFETs) with improved performance and stability. This study highlights the role of unintentional contaminants in organic electronic devices, and demonstrates that certain stringent processing conditions need to be met to avoid scientific misinterpretation, ensure device reproducibility, and facilitate performance stability. The experimental procedures and conditions used herein are typical of those used by many groups in the field of solution-processed organic semiconductors. Therefore, the insights gained into the effects of contamination are likely to be broadly applicable to studies, not just of OFETs, but also of other devices based on these materials.

Differential Volatile Organic Compound Expression in the Interaction of Daldinia eschscholtzii and Mycena citricolor

Fungi exhibit a wide range of ecological guilds, but those that live within the inner tissues of plants (also known as endophytes) are particularly relevant due to the benefits they sometimes provide to their hosts, such as herbivory deterrence, disease protection, and growth promotion. Recently, endophytes have gained interest as potential biocontrol agents against crop pathogens, for example, coffee plants (Coffea arabica). Published results from research performed in our laboratory showed that endophytic fungi isolated from wild Rubiaceae plants were effective in reducing the effects of the American leaf spot of coffee (Mycena citricolor). One of these isolates (GU11N) from the plant Randia grandifolia was identified as Daldinia eschscholtzii (Xylariales). Its antagonism mechanisms, effects, and chemistry against M. citricolor were investigated by analyzing its volatile profile alone and in the presence of the pathogen in contactless and dual culture assays. The experimental design involved direct sampling of agar plugs in vials for headspace (HS) and headspace solid-phase microextraction (HS-SPME) gas chromatography-mass spectrometry (GC-MS) analysis. Additionally, we used ultrahigh-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS/MS) to identify nonvolatile compounds from organic extracts of the mycelia involved in the interaction. Results showed that more volatile compounds were identified using HS-SPME (39 components) than those by the HS technique (13 components), sharing only 12 compounds. Statistical tests suggest that D. eschscholtzii inhibited the growth of M. citricolor through the release of VOCs containing a combination of 1,8-dimethoxynapththalene and terpene compounds affecting M. citricolor pseudopilei. The damaging effects of 1,8-dimethoxynaphthalene were corroborated in an in vitro test against M. citricolor pseudopilei; scanning electron microscopy (SEM) photographs confirmed structural damage. After analyzing the UHPLC-HRMS/MS data, a predominance of fatty acid derivatives was found among the putatively identified compounds. However, a considerable proportion of features (37.3%) remained unannotated. In conclusion, our study suggests that D. eschscholtzii has potential as a biocontrol agent against M. citricolor and that 1,8-dimethoxynaphthalene contributes to the observed damage to the pathogen's reproductive structures.

Dissolved organic metabolite extraction from high-salt media

We describe considerations and strategies for developing a nuclear magnetic resonance (NMR) sample preparation method to extract low molecular weight metabolites from high-salt spent media in a model coculture system of phytoplankton and marine bacteria. Phytoplankton perform half the carbon fixation and oxygen generation on Earth. A substantial fraction of fixed carbon becomes part of a metabolite pool of small molecules known as dissolved organic matter (DOM), which are taken up by marine bacteria proximate to phytoplankton. There is an urgent need to elucidate these metabolic exchanges due to widespread anthropogenic transformations on the chemical, phenotypic, and species composition of seawater. These changes are increasing water temperature and the amount of CO₂ absorbed by the ocean at energetic costs to marine microorganisms. Little is known about the metabolite-mediated, structured interactions occurring between phytoplankton and associated marine bacteria, in part because of challenges in studying high-salt solutions on various analytical platforms. NMR analysis is problematic due to the high-salt content of both natural seawater and culture media for marine microbes. High-salt concentration degrades the performance of the radio frequency coil, reduces the efficiency of some pulse sequences, limits signal-to-noise, and prolongs experimental time. The method described herein can reproducibly extract low molecular weight DOM from small-volume, high-salt cultures. It is a promising tool for elucidating metabolic flux between marine microorganisms and facilitates genetic screens of mutant microorganisms.

Guided Isolation of An Uncommon Cembranoid Orthoester, Sarcotortin A, and Three Skeletal Diverse Terpenoids from the Hainan Soft Coral Sarcophyton tortuosum Based on Molecular Networking Strategy

Applying the emerging molecular networking strategy, an uncommon cembranoid orthoester, sarcotortin A (1), featuring a 3/14/8/5-fused scaffold, an unusual eunicellane-type diterpenoid, sarcotorolide A (2), and two new biscembranoids, ximaolides M and N (7 and 8), along with nine known terpenoids 3-6 and 9-13 were isolated from the Hainan soft coral Sarcophyton tortuosum. The structure and absolute configuration of all new compounds were established by a combination of spectroscopic data, X-ray diffraction analysis, and/or quantum chemical computational approaches. The plausible biogenetic relationship among these skeletally different terpenoids was proposed and discussed. In in vitro bioassay, new compound 7 exhibited a remarkable inhibitory activity against protein tyrosine phosphatases 1B (PTP1B) with the IC₅₀ value of 8.06 μM. In addition, compounds 4 and 10 displayed significant inhibitory effects on lipopolysaccharide (LPS)-induced inflammatory responses in RAW264.7 macrophages cells with the IC₅₀ values of 19.13 and 16.45 μM, respectively. Compound 9 showed interesting cytotoxicity against H1975, MDA-MB231, A549, and H1299 cancer cell lines with IC₅₀ values of 31.59, 34.96, 43.87, and 27.93 μM, respectively.

Identifying molecular functional groups of organic compounds by deep learning of NMR data

We preprocess the raw nuclear magnetic resonance (NMR) spectrum and extract key features by using two different methodologies, called equidistant sampling and peak sampling for subsequent substructure pattern recognition. We also provide a strategy to address the imbalance issue frequently encountered in statistical modeling of NMR data set and establish two conventional support vector machine (SVM) and K-nearest neighbor (KNN) models to assess the capability of two feature selections, respectively. Our results in this study show that the models using the selected features of peak sampling outperform those using equidistant sampling. Then we build the recurrent neural network (RNN) model trained by data collected from peak sampling. Furthermore, we illustrate the easier optimization of hyperparameters and the better generalization ability of the RNN deep learning model by detailed comparison with traditional machine learning SVM and KNN models.

The toxic cosmopolitan cyanobacteria Moorena producens: insights into distribution, ecophysiology and toxicity

Moorena producens is a benthic filamentous cyanobacteria that has been widely documented for its toxicity. This cyanobacterium colonizes both temperate (37%) and tropical (63%) regions, making it a cosmopolitan cyanobacterium with a global distribution. M. producens grows across coral reefs in multiple locations but recurringly blooms in Queensland, Australia. Today, nuisance blooms of M. producens have resulted in major disruptions to recreational activities along coastal areas and are known to cause adverse effects on organism and human health upon contact or ingestion. Specifically, marine organisms such as the green turtle Chelonia mydas and hawksbill turtle Eretmochelys imbricata were fatally poisoned by M. producens after consumption of this cyanobacterium. Reports record a range of effects on human health, from pain and blistering or even death upon ingestion of contaminated seafood. Blooms of M. producens are triggered by influxes of nitrogen, phosphate and iron, from surrounding coastal runoffs or sewage effluents. Additions of these nutrients can result in an increase in growth rate by 4-16 times. Iron bioavailability also plays a crucial role in bloom formation. A total of 231 natural products from 66 groups were identified from M. producens, with the three dominant groups: malyngamides, microcolins and dolastatins. These bioactive secondary metabolites have displayed toxicities against a range of carcinoma cell lines and organisms such as brine shrimp Artemia salina and goldfish Carassius auratus. This review provides a thorough insight to the distribution, ecophysiology and toxicity of M. producens, with reports on bloom events and implications on organism and human health.

Expanding the utility of Marfey's analysis by using HPLC-SPE-NMR to determine the Cβ configuration of threonine and isoleucine residues in natural peptides

The determination of amino acid chirality in natural peptides is typically addressed by Marfey's analysis. This approach relies on the complete hydrolysis of the peptide followed by the reaction of the resulting amino acid pool with Marfey's reagent, a chiral derivatizing agent which turns amino acid enantiomers into diastereomeric pairs which can be resolved by conventional reversed-phase HPLC. However, for certain amino acids possessing a second chiral centre at C_β, the discrimination between the two possible epimers may still be challenging due to the lack of chromatographic resolution. Such is the case of isoleucine and threonine which can also be found in natural nonribosomal peptides as their allo-diastereomers. We describe a new approach based on the extension of Marfey's analysis using HPLC-SPE-NMR to sort out this challenge. Marfey's derivatives of these epimeric amino acids at C_β can be differentiated by their distinct NMR spectra. Thus, simple comparison of the NMR spectra of trapped HPLC peaks with the corresponding spectra of standards enables the unambiguous assignment of the absolute configuration at the second chiral centre in such cases. The general applicability of this approach is showcased for two model cyclic peptides bearing L-Ile and L-Thr.

NMR and Metabolomics-A Roadmap for the Future

Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These metabolic changes are measured with various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods are becoming increasingly popular in the field of metabolomics (accounting for more than 70% of published metabolomics studies to date), there are considerable benefits and advantages to NMR-based methods for metabolomic studies. In fact, according to PubMed, more than 926 papers on NMR-based metabolomics were published in 2021-the most ever published in a given year. This suggests that NMR-based metabolomics continues to grow and has plenty to offer to the scientific community. This perspective outlines the growing applications of NMR in metabolomics, highlights several recent advances in NMR technologies for metabolomics, and provides a roadmap for future advancements.

Isolation and Total Synthesis of Beru'amide, an Antitrypanosomal Polyketide from a Marine Cyanobacterium Okeania sp

A 68 μg amount of an acyclic polyketide, named beru'amide, was isolated from a marine cyanobacterium Okeania sp. Beru'amide contains six unique moieties in its relatively small skeleton. By applying several cutting-edge techniques, including DFT-based chemical shift calculations, we achieved the structure determination and the total synthesis of this highly functionalized scarce natural product. Furthermore, beru'amide was shown to have strong antitrypanosomal activity.

Combining Activity Profiling with Advanced Annotation to Accelerate the Discovery of Natural Products Targeting Oncogenic Signaling in Melanoma

The discovery of bioactive natural products remains a time-consuming and challenging task. The ability to link high-confidence metabolite annotations in crude extracts with activity would be highly beneficial to the drug discovery process. To address this challenge, HPLC-based activity profiling and advanced UHPLC-HRMS/MS metabolite profiling for annotation were combined to leverage the information obtained from both approaches on a crude extract scaled down to the submilligram level. This strategy was applied to a subset of an extract library screening aiming to identify natural products inhibiting oncogenic signaling in melanoma. Advanced annotation and data organization enabled the identification of compounds that were likely responsible for the activity in the extracts. These compounds belonged to two different natural product scaffolds, namely, brevipolides from a Hyptis brevipes extract and methoxylated flavonoids identified in three different extracts of Hyptis and Artemisia spp. Targeted isolation of these prioritized compounds led to five brevipolides and seven methoxylated flavonoids. Brevipolide A (1) and 6-methoxytricin (9) were the most potent compounds from each chemical class and displayed AKT activity inhibition with an IC₅₀ of 17.6 ± 1.6 and 4.9 ± 0.2 μM, respectively.

Feature-Based Molecular Networking Discovery of Bromopyrrole Alkaloids from the Marine Sponge Agelas dispar

Investigation of the marine sponge Agelas dispar MeOH fractions using feature-based molecular networking, dereplication, and isolation led to the discovery of new bromopyrrole-derived metabolites. An in-house library of bromopyrrole alkaloids previously isolated from A. dispar and Dictyonella sp. was utilized, along with the investigation of an MS/MS fragmentation of these compounds. Our strategy led to the isolation and identification of the disparamides A-C (1-3), with a novel carbon skeleton. Additionally, new dispyrins B-F (4-8) and nagelamides H2 and H3 (9 and 10) and known nagelamide H (11), citrinamine B (12), ageliferin (13), bromoageliferin (14), and dibromoageliferin (15) were also isolated and identified by analysis of spectroscopic data. Analysis of MS/MS fragmentation data and molecular networking analysis indicated the presence of hymenidin (16), oroidin (17), dispacamide (18), monobromodispacamide (19), keramadine (20), longamide B (21), methyl ester of longamide B (22), hanishin (23), methyl ester of 3-debromolongamide B (24), and 3-debromohanishin (25). Antibacterial activity of ageliferin (13), bromoageliferin (14), and dibromoageliferin (15) was evaluated against susceptible and multi-drug-resistant ESKAPE pathogenic bacteria Klabsiella pneumoniae, Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Acinetobacter baumannii, and Enterococcus faecalis. Dibromoageliferin (15) displayed the most potent antimicrobial activity against all tested susceptible and MDR strains. Compounds 13-15 presented no significant hemolytic activity up to 100 μM.

Statistical evaluation of simulated NMR data of flexible molecules

A new probability score-named χ-probability-is introduced for evaluating the fit of mixed NMR datasets to calculate molecular model ensembles, in order to answer challenging structural questions such as the determination of stereochemical configurations. Similar to the DP4 parameter, the χ-probability is based on Bayes theorem and expresses the probability that an experimental NMR dataset fits to a given individual within a finite set of candidate structures or configurations. Here, the χ-probability is applied to single out the correct configuration in four example cases, with increasing complexity and conformational mobility. The NMR data (which include RDCs, NOE distances and ³J couplings) are calculated from MDOC (Molecular Dynamics with Orientational Constraints) trajectories and are investigated against experimentally measured data. It is demonstrated that this approach singles out the correct stereochemical configuration with probabilities more than 98%, even for highly mobile molecules. In more demanding cases, a decisive χ-probability test requires that the datasets include high-quality NOE distances in addition to RDC values.

High-Resolution Molecular-Level Characterization of a Blanket Bog Peat Profile

To understand peatland carbon-cycling processes ultimately requires the ability to track changes occurring on the molecular-level. In this study, we profile a peat core taken from the world's largest blanket bog, Flow Country, Scotland, using physicochemical properties, ATR-FTIR, solid/liquid-state NMR, and solid/liquid-state FT-ICR-MS. Air-dried peat and labile and recalcitrant peat extracts, including pore water dissolved organic matter (PW-DOM), are analyzed and the merits of each technique are discussed. Solid-state NMR demonstrated changing distribution of compound classes with core depth and water table, the latter not picked up by IR. Liquid-state NMR and MS both demonstrated variations in molecular composition along the core depth in all phases and extracts. Contrary to previous reports, the composition of PW-DOM varied with depth. Major compounds, some previously unreported, identified by 1D/2D NMR occurred throughout the core, suggesting the existence of hot spots of microbial activity/compound accumulation. Offering complementary views, the techniques provided evidence of gradual molecular level changes with age, zonation due to the water table, and hot spots due to microbial activity. This study provides new insights into the molecular signatures of peat layers and establishes the foundation for examining peat function and health at the molecular-level.

Accelerated 13C detection by concentrating the NMR sample in a biphasic solvent system

CDCl₃ is the most frequently used solvent for the NMR investigation of organic compounds. Busy chemistry labs need to investigate hundreds of compounds daily. While ¹H NMR investigation takes a couple of minutes, recording ¹³C NMR spectra necessitates hours of signal averaging due to the low abundance and low sensitivity of ¹³C nuclei. The longer acquisition time for ¹³C NMR results in a loss of precious spectrometer time in a shared multi-user environment. A regular 5 mm o.d. NMR tube is the most commonly used tube for NMR in organic chemistry labs and is also the cheapest option. We show that for analytes soluble in the CDCl₃ solvent using a regular 5 mm o.d. NMR tube, the speed of ¹³C observation can be enhanced by a factor of two by resorting to a sample preparation method that employs a biphasic system made of H₂O or D₂O at the top of another layer of CDCl₃. By using the biphasic system of two immiscible solvents, the analyte can be concentrated in the CDCl₃ layer (within the more sensitive volume of the NMR coil), resulting in the improvement of the signal to noise ratio (SNR) by a factor of up to 1.8 for ¹³C and 2D ¹H-¹³C HSQC spectra, which results in more than two-fold reduction in the experimental time. ¹H NMR and other 2D NMR also get a sensitivity boost. The amount of CDCl₃ required for sample preparation can also be reduced by 40% using this biphasic system (CDCl₃/H₂O). Sample preparation in such an immiscible biphasic system is effortless and straightforward. The performance of such biphasic samples is closer to that of Shigemi tubes and better than that of 3 mm o.d. tubes.

Recent Developments Toward Integrated Metabolomics Technologies (UHPLC-MS-SPE-NMR and MicroED) for Higher-Throughput Confident Metabolite Identifications

Metabolomics has emerged as a powerful discipline to study complex biological systems from a small molecule perspective. The success of metabolomics hinges upon reliable annotations of spectral features obtained from MS and/or NMR. In spite of tremendous progress with regards to analytical instrumentation and computational tools, < 20% of spectral features are confidently identified in most untargeted metabolomics experiments. This article explores the integration of multiple analytical instruments such as UHPLC-MS/MS-SPE-NMR and the cryo-EM method MicroED to achieve large-scale and confident metabolite identifications in a higher-throughput manner. UHPLC-MS/MS-SPE allows for the simultaneous automated purification of metabolites followed by offline structure elucidation and structure validation by NMR and MicroED. Large-scale study of complex metabolomes such as that of the model plant legume Medicago truncatula can be achieved using an integrated UHPLC-MS/MS-SPE-NMR metabolomics platform. Additionally, recent developments in MicroED to study structures of small organic molecules have enabled faster, easier and precise structure determinations of metabolites. A MicroED small molecule structure elucidation workflow (e.g., crystal screening, sample preparation, data collection and data processing/structure determination) has been described. Ongoing MicroED methods development and its future scope related to structure elucidation of specialized metabolites and metabolomics are highlighted. The incorporation of MicroED with a UHPLC-MS/MS-SPE-NMR instrumental ensemble offers the potential to accelerate and achieve higher rates of metabolite identification.

Thirtieth Anniversary of the Discovery of Laxaphycins. Intriguing Peptides Keeping a Part of Their Mystery

Lipopeptides are a class of compounds generally produced by microorganisms through hybrid biosynthetic pathways involving non-ribosomal peptide synthase and a polyketyl synthase. Cyanobacterial-produced laxaphycins are examples of this family of compounds that have expanded over the past three decades. These compounds benefit from technological advances helping in their synthesis and characterization, as well as in deciphering their biosynthesis. The present article attempts to summarize most of the articles that have been published on laxaphycins. The current knowledge on the ecological role of these complex sets of compounds will also be examined.

Natural Products, the Fourth Industrial Revolution, and the Quintuple Helix

The profound interconnectedness of the sciences and technologies embodied in the Fourth Industrial Revolution is discussed in terms of the global role of natural products, and how that interplays with the development of sustainable and climate-conscious practices of cyberecoethnopharmacolomics within the Quintuple Helix for the promotion of a healthier planet and society.

Rapid nuclear magnetic resonance data acquisition with improved resolution and sensitivity for high-throughput metabolomic analysis

Nuclear magnetic resonance (NMR)-based metabolomics has witnessed rapid advancements in recent years with the continuous development of new methods to enhance the sensitivity, resolution, and speed of data acquisition. Some of the approaches were earlier used for peptide and protein resonance assignments and have now been adapted to metabolomics. At the same time, new NMR methods involving novel data acquisition techniques, suited particularly for high-throughput analysis in metabolomics, have been developed. In this review, we focus on the different sampling strategies or data acquisition methods that have been developed in our laboratory and other groups to acquire NMR spectra rapidly with high sensitivity and resolution for metabolomics. In particular, we focus on the use of multiple receivers, phase modulation NMR spectroscopy, and fast-pulsing methods for identification and assignments of metabolites.

Biophysical characterization of antibacterial compounds derived from pathogenic fungi Ganoderma boninense

There have been relatively few studies which support a link between Ganoderma boninense, a phytopathogenic fungus that is particularly cytotoxic and pathogenic to plant tissues and roots, and antimicrobial compounds. We previously observed that liquid-liquid extraction (LLE) using chloroformmethanol-water at a ratio (1:1:1) was superior at detecting antibacterial activities and significant quantities of antibacterial compounds. Herein, we demonstrate that antibacterial secondary metabolites are produced from G. boninense mycelia. Antibacterial compounds were monitored in concurrent biochemical and biophysical experiments. The combined methods included high performance thin-layer chromatography (HPTLC), gas chromatography-mass spectrometry (GC-MS), high-performance liquid chromatography (HPLC), fourier transform infrared (FTIR), and nuclear magnetic resonance (NMR) spectroscopy. The antibacterial compounds derived from mycelia with chloroform-methanol extraction through LLE were isolated via a gradient solvent elution system using HPTLC. The antibacterial activity of the isolated compounds was observed to be the most potent against Staphylococcus aureus ATCC 25923 and multidrug-resistant S. aureus NCTC 11939. GC-MS, HPLC, and FTIR analysis confirmed two antibacterial compounds, which were identified as 4,4,14α-trimethylcholestane (m/z = 414.75; lanostane, C₃₀H₅₄) and ergosta-5,7,22-trien-3β-ol (m/z = 396.65; ergosterol, C₂₈H₄₄O). With the aid of spectroscopic evaluations, ganoboninketal (m/z = 498.66, C₃₀H₄₂O₆), which belongs to the 3,4-seco-27-norlanostane triterpene family, was additionally characterized by 2D-NMR analysis. Despite the lack of antibacterial potential exhibited by lanostane; both ergosterol and ganoboninketal displayed significant antibacterial activities against bacterial pathogens. Results provide evidence for the existence of bioactive compounds in the mycelia of the relatively unexplored phytopathogenic G. boninense, together with a robust method for estimating the corresponding potent antibacterial secondary metabolites.

Exploration of continuous-flow benchtop NMR acquisition parameters and considerations for reaction monitoring

This study focused on fundamental data acquisition parameter selection for a benchtop nuclear magnetic resonance (NMR) system with continuous flow, applicable for reaction monitoring. The effect of flow rate on the mixing behaviors within a flow cell was observed, along with an exponential decay relationship between flow rate and the apparent spin-lattice relaxation time (T1*) of benzaldehyde. We also monitored sensitivity (as determined by signal-to-noise ratios; SNRs) under various flow rates, analyte concentrations, and temperatures of the analyte flask. Results suggest that a maximum SNR can be achieved with low to medium flow rates and higher analyte concentrations. This was consistent with data collected with parameters that promote either slow or fast data acquisition. We further consider the effect of these conditions on the analyte's residence time, T1*, and magnetic field inhomogeneity that is a product of continuous flow. Altogether, our results demonstrate how fundamental acquisition parameters can be manipulated to achieve optimal data acquisition in continuous-flow NMR systems.

EBC-232 and 323: A Structural Conundrum Necessitating Unification of Five In Silico Prediction and Elucidation Methods

Structurally unique halimanes EBC-232 and EBC-323, isolated from the Australian rainforest plant Croton insularis, proved considerably difficult to elucidate. The two diastereomers, which consist an unusual oxo-6,7-spiro ring system fused to a dihydrofuran, were solved by unification and consultation of five in silico NMR elucidation and prediction methods [i.e., ACDLabs, olefin strain energy (OSE), DP4, DU8+ and TD DFT CD]. Structure elucidation challenges of this nature are prime test case examples for empowering future AI learning in structure elucidation.

Synchronous bond molecular dynamics of conjugated chlorocyclopropyl alk-yn-enes revealed by ECD and UV-vis

Chlorocyclopropanes (CCPs) conjugated to alk-yn-enes occur in a unique family of polyketide natural products from marine sponges. Synthesis of several optically enriched analogs of CCPs and measurement of their UV-vis spectra and electronic circular dichroism (ECD) spectra reveal unusually strong hyperconjugation that constrains and aligns the cyclopropyl C-C bond with the π-plane of the distal ene-bond. This alignment imposes a barrier to rotation of at least 5.0 kcal·mol-1 . Comparison of red-shifted Cotton effects in chiral CCPs show the barrier is independent of alkene substituent and establishes an empirical rule for assignment of other CCP-containing natural products.

Creating and screening natural product libraries

Covering: up to 2020The National Cancer Institute of the United States (NCI) has initiated a Cancer Moonshot program entitled the NCI Program for Natural Product Discovery. As part of this effort, the NCI is producing a library of 1 000 000 partially purified natural product fractions which are being plated into 384-well plates and provided to the research community free of charge. As the first 326 000 of these fractions have now been made available, this review seeks to describe the general methods used to collect organisms, extract those organisms, and create a prefractionated library. Importantly, this review also details both cell-based and cell-free bioassay methods and the adaptations necessary to those methods to productively screen natural product libraries. Finally, this review briefly describes post-screen dereplication and compound purification and scale up procedures which can efficiently identify active compounds and produce sufficient quantities of natural products for further pre-clinical development.

Advances in exploring the therapeutic potential of marine natural products

Marine natural products represent novel and diverse chemotypes that serve as templates for the discovery and development of therapeutic agents with distinct mechanisms of action. These genetically encoded compounds produced by an evolutionary optimized biosynthetic machinery are usually quite complex and can be difficult to recreate in the laboratory. The isolation from the source organism results in limited amount of material; however, the development of advanced NMR technologies and dereplication strategies has enabled the structure elucidation on small scale. In order to rigorously explore the therapeutic potential of marine natural products and advance them further, the biological characterization has to keep pace with the chemical characterization. The limited marine natural product supply has been a serious challenge for thorough investigation of the biological targets. Several marine drugs have reached the markets or are in clinical trials, where those challenges have been overcome, including through the development of scalable syntheses. However, the identification of mechanisms of action of marine natural products early in the discovery process is potentially game changing, since effectively linking marine natural products to potential therapeutic applications in turn triggers motivation to tackle challenging syntheses and solve the supply problem. An increasing number of sensitive technologies and methods have been developed in recent years, some of which have been successfully applied to marine natural products, increasing the value of these compounds with respect to their biomedical utility. In this review, we discuss advances in overcoming the bottlenecks in marine natural product research, emphasizing on the development and advances of diverse target identification technologies applicable for marine natural product research.

High-resolution pure shift NMR spectroscopy offers better metabolite discrimination in food quality analysis

PSYCHE homonuclear decoupling, a prominent pure shift NMR method, is successfully applied to adulteration discrimination of honey and geographical originality identification of tea. Effects of homonuclear couplings are efficiently suppressed, producing resolution-enhanced spectra. The pair wise honey and tea samples are well separated in OPLS-DA models with high predictability. Due to the well-resolved and accurate assignment of singlet resonances after decoupling, PSYCHE is advantageous in the identification of differential components and accurate quantification of compound concentrations presented by enhanced volcano and Beeswarm plots of honey samples, while the analysis of NOESY is easily interfered by overlapped resonances, which is further proved by the STOCSY analysis, displaying the spectral stability and reproducibility. Experimental results show that PSYCHE can improve the spectral resolution of natural complex products such as honey and tea and be combined with multivariate statistical analysis and serve as a supplementary technique to the standard methods, especially for samples systems composed by a few high-content compounds.

Discovery and characterization of natural products that act as pheromones in fish

Covering: up to 2018 Fish use a diverse collection of molecules to communicate with conspecifics. Since Karlson and Lüscher termed these molecules 'pheromones', chemists and biologists have joined efforts to characterize their structures and functions. In particular, the understanding of insect pheromones developed at a rapid pace, set, in part, by the use of bioassay-guided fractionation and natural product chemistry. Research on vertebrate pheromones, however, has progressed more slowly. Initially, biologists characterized fish pheromones by screening commercially available compounds suspected to act as pheromones based upon their physiological function. Such biology-driven screening has proven a productive approach to studying pheromones in fish. However, the many functions of fish pheromones and diverse metabolites that fish release make predicting pheromone identity difficult and necessitate approaches led by chemistry. Indeed, the few cases in which pheromone identification was led by natural product chemistry indicated novel or otherwise unpredicted compounds act as pheromones. Here, we provide a brief review of the approaches to identifying pheromones, placing particular emphasis on the promise of using natural product chemistry together with assays of biological activity. Several case studies illustrate bioassay-guided fractionation as an approach to pheromone identification in fish and the unexpected diversity of pheromone structures discovered by natural product chemistry. With recent advances in natural product chemistry, bioassay-guided fractionation is likely to unveil an even broader collection of pheromone structures and enable research that spans across disciplines.

Challenges in the configuration assignment of natural products. A case-selective perspective

An overview by a case study approach on the currently available methods for the configurational analysis of natural products.

Approaches for the isolation and identification of hydrophilic, light-sensitive, volatile and minor natural products

Water-soluble, volatile, minor and photosensitive natural products are yet poorly known, and this review discusses the literature reporting the isolation strategies for some of these metabolites.

UHPLC-QTOF-MS/MS-SPE-NMR: A Solution to the Metabolomics Grand Challenge of Higher-Throughput, Confident Metabolite Identifications

Metabolomics represents a powerful, complementary approach for studying biological system responses to various biotic and abiotic stimuli. A major challenge in metabolomics is the lack of reliable annotations for all metabolites detected in complex MS and/or NMR data. To meet this challenge, we have developed an integrated UHPLC-QTOF-MS/MS-SPE-NMR system for higher-throughput metabolite identifications, which provides advanced biological context and enhances the scientific value of metabolomics data for understanding systems biology. This integrated instrumental method is less labor-intensive and more cost-effective than conventional individual methods (LC; MS; SPE; NMR). It enables the simultaneous purification and identification of primary and secondary metabolites present in biological samples. In this chapter, we describe the configuration and use of UHPLC-MS/MS-SPE-NMR in metabolite analyses ranging from sample extraction to higher-throughput metabolite annotation. With the integrated UHPLC-QTOF-MS/MS-SPE-NMR method, we have purified and confidently identified more than 100 previously known as well as unknown triterpene and flavonoid glycosides while noting that most of the identified compounds are not commercially available.

Contribution of Untargeted Metabolomics for Future Assessment of Biotech Crops

The nutritional value and safety of food crops are ultimately determined by their chemical composition. Recent developments in the field of metabolomics have made it possible to characterize the metabolic profile of crops in a comprehensive and high-throughput manner. Here, we propose that state-of-the-art untargeted metabolomics technology should be leveraged for safety assessment of new crop products. We suggest generally applicable experimental design principles that facilitate the efficient and rigorous identification of both intended and unintended metabolic alterations associated with a newly engineered trait. Our proposition could contribute to increased transparency of the safety assessment process for new biotech crops.

NCI Program for Natural Product Discovery: A Publicly-Accessible Library of Natural Product Fractions for High-Throughput Screening

The US National Cancer Institute's (NCI) Natural Product Repository is one of the world's largest, most diverse collections of natural products containing over 230,000 unique extracts derived from plant, marine, and microbial organisms that have been collected from biodiverse regions throughout the world. Importantly, this national resource is available to the research community for the screening of extracts and the isolation of bioactive natural products. However, despite the success of natural products in drug discovery, compatibility issues that make extracts challenging for liquid handling systems, extended timelines that complicate natural product-based drug discovery efforts and the presence of pan-assay interfering compounds have reduced enthusiasm for the high-throughput screening (HTS) of crude natural product extract libraries in targeted assay systems. To address these limitations, the NCI Program for Natural Product Discovery (NPNPD), a newly launched, national program to advance natural product discovery technologies and facilitate the discovery of structurally defined, validated lead molecules ready for translation will create a prefractionated library from over 125,000 natural product extracts with the aim of producing a publicly-accessible, HTS-amenable library of >1,000,000 fractions. This library, representing perhaps the largest accumulation of natural-product based fractions in the world, will be made available free of charge in 384-well plates for screening against all disease states in an effort to reinvigorate natural product-based drug discovery.

Small Molecule Accurate Recognition Technology (SMART) to Enhance Natural Products Research

Various algorithms comparing 2D NMR spectra have been explored for their ability to dereplicate natural products as well as determine molecular structures. However, spectroscopic artefacts, solvent effects, and the interactive effect of functional group(s) on chemical shifts combine to hinder their effectiveness. Here, we leveraged Non-Uniform Sampling (NUS) 2D NMR techniques and deep Convolutional Neural Networks (CNNs) to create a tool, SMART, that can assist in natural products discovery efforts. First, an NUS heteronuclear single quantum coherence (HSQC) NMR pulse sequence was adapted to a state-of-the-art nuclear magnetic resonance (NMR) instrument, and data reconstruction methods were optimized, and second, a deep CNN with contrastive loss was trained on a database containing over 2,054 HSQC spectra as the training set. To demonstrate the utility of SMART, several newly isolated compounds were automatically located with their known analogues in the embedded clustering space, thereby streamlining the discovery pipeline for new natural products.

Use of Hybrid Capillary Tube Apparatus on 400 MHz NMR for Quantitation of Crucial Low-Quantity Metabolites Using aSICCO Signal

Metabolites of new chemical entities can influence safety and efficacy of a molecule and often times need to be quantified in preclinical studies. However, synthetic standards of metabolites are very rarely available in early discovery. Alternate approaches such as biosynthesis need to be explored to generate these metabolites. Assessing the quantity and purity of these small amounts of metabolites with a nondestructive analytical procedure becomes crucial. Quantitative NMR becomes the method of choice for these samples. Recent advances in high-field NMR (>500 MHz) with the use of cryoprobe technology have helped to improve sensitivity for analysis of small microgram quantity of such samples. However, this type of NMR instrumentation is not routinely available in all laboratories. To analyze microgram quantities of metabolites on a routine basis with lower-resolution 400 MHz NMR instrument fitted with a broad band fluorine observe room temperature probe, a novel hybrid capillary tube setup was developed. To quantitate the metabolite in the sample, an artificial signal insertion for calculation of concentration observed (aSICCO) method that introduces an internally calibrated mathematical signal was used after acquiring the NMR spectrum. The linearity of aSICCO signal was established using ibuprofen as a model analyte. The limit of quantification of this procedure was 0.8 mM with 10 K scans that could be improved further with the increase in the number of scans. This procedure was used to quantify three metabolites-phenytoin from fosphenytoin, dextrophan from dextromethorphan, and 4-OH-diclofenac from diclofenac-and is suitable for minibiosynthesis of metabolites from in vitro systems.

qNMR for profiling the production of fungal secondary metabolites

Analysis of complex mixtures is a common challenge in natural products research. Quantitative nuclear magnetic resonance spectroscopy offers analysis of complex mixtures at early stages and with benefits that are orthogonal to more common methods of quantitation, including ultraviolet absorption spectroscopy and mass spectrometry. Several experiments were conducted to construct a methodology for use in analysis of extracts of fungal cultures. A broadly applicable method was sought for analysis of both pure and complex samples through use of an externally calibrated method. This method has the benefit of not contaminating valuable samples with the calibrant, and it passed scrutiny for line fitting and reproducibility. The method was implemented to measure the yield of griseofulvin and dechlorogriseofulvin from three fungal isolates. An isolate of Xylaria cubensis (coded MSX48662) was found to biosynthesize griseofulvin in the greatest yield, 149 ± 8 mg per fermentation, and was selected for further supply experiments. Copyright © 2016 John Wiley & Sons, Ltd.

Using natural products for drug discovery: the impact of the genomics era

INTRODUCTION

Evolutionarily selected over billions of years for their interactions with biomolecules, natural products have been and continue to be a major source of pharmaceuticals. In the 1990s, pharmaceutical companies scaled down their natural product discovery programs in favor of synthetic chemical libraries due to major challenges such as high rediscovery rates, challenging isolation, and low production titers. Propelled by advances in DNA sequencing and synthetic biology technologies, insights into microbial secondary metabolism provided have inspired a number of strategies to address these challenges. Areas covered: This review highlights the importance of genomics and metagenomics in natural product discovery, and provides an overview of the technical and conceptual advances that offer unprecedented access to molecules encoded by biosynthetic gene clusters. Expert opinion: Genomics and metagenomics revealed nature's remarkable biosynthetic potential and her vast chemical inventory that we can now prioritize and systematically mine for novel chemical scaffolds with desirable bioactivities. Coupled with synthetic biology and genome engineering technologies, significant progress has been made in identifying and predicting the chemical output of biosynthetic gene clusters, as well as in optimizing cluster expression in native and heterologous host systems for the production of pharmaceutically relevant metabolites and their derivatives.

Natural Products Diversity of Marine Ascidians (Tunicates; Ascidiacea) and Successful Drugs in Clinical Development

This present study reviewed the chemical diversity of marine ascidians and their pharmacological applications, challenges and recent developments in marine drug discovery reported during 1994-2014, highlighting the structural activity of compounds produced by these specimens. Till date only 5% of living ascidian species were studied from <3000 species, this study represented from family didemnidae (32%), polyclinidae (22%), styelidae and polycitoridae (11-12%) exhibiting the highest number of promising MNPs. Close to 580 compound structures are here discussed in terms of their occurrence, structural type and reported biological activity. Anti-cancer drugs are the main area of interest in the screening of MNPs from ascidians (64%), followed by anti-malarial (6%) and remaining others. FDA approved ascidian compounds mechanism of action along with other compounds status of clinical trials (phase 1 to phase 3) are discussed here in. This review highlights recent developments in the area of natural products chemistry and biotechnological approaches are emphasized.

Structure Elucidation of Antibiotics by Nmr Spectroscopy

Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for the structure elucidation of antibiotics in solution. Over the past 30 years there have been numerous publications describing the use of NMR to characterize naturally derived or synthetic antibiotics. A large number of one-dimensional (1D) and two-dimensional (2D) NMR methods are available today and the list continues to expand. In this chapter, we will consider the key NMR experiments that provide useful information for compound structure elucidation.

Towards single egg toxicity screening using microcoil NMR

Planar NMR microcoils are evaluated, their application to single eggs is demonstrated, and their potential for studying smaller single cells is discussed.

Current and Future Perspectives on the Structural Identification of Small Molecules in Biological Systems

Although significant advances have been made in recent years, the structural elucidation of small molecules continues to remain a challenging issue for metabolite profiling. Many metabolomic studies feature unknown compounds; sometimes even in the list of features identified as "statistically significant" in the study. Such metabolic "dark matter" means that much of the potential information collected by metabolomics studies is lost. Accurate structure elucidation allows researchers to identify these compounds. This in turn, facilitates downstream metabolite pathway analysis, and a better understanding of the underlying biology of the system under investigation. This review covers a range of methods for the structural elucidation of individual compounds, including those based on gas and liquid chromatography hyphenated to mass spectrometry, single and multi-dimensional nuclear magnetic resonance spectroscopy, and high-resolution mass spectrometry and includes discussion of data standardization. Future perspectives in structure elucidation are also discussed; with a focus on the potential development of instruments and techniques, in both nuclear magnetic resonance spectroscopy and mass spectrometry that, may help solve some of the current issues that are hampering the complete identification of metabolite structure and function.

Characterization and Synthesis of Eudistidine C, a Bioactive Marine Alkaloid with an Intriguing Molecular Scaffold

An extract of Eudistoma sp. provided eudistidine C (1), a heterocyclic alkaloid with a novel molecular framework. Eudistidine C (1) is a racemic natural product composed of a tetracyclic core structure further elaborated with a p-methoxyphenyl group and a phenol-substituted aminoimidazole moiety. This compound presented significant structure elucidation challenges due to the large number of heteroatoms and fully substituted carbons. These issues were mitigated by application of a new NMR pulse sequence (LR-HSQMBC) optimized to detect four- and five-bond heteronuclear correlations and the use of computer-assisted structure elucidation software. Synthesis of eudistidine C (1) was accomplished in high yield by treating eudistidine A (2) with 4(2-amino-1H-imidazol-5-yl)phenol (4) in DMSO. Synthesis of eudistidine C (1) confirmed the proposed structure and provided material for further biological characterization. Treatment of 2 with various nitrogen heterocycles and electron-rich arenes provided a series of analogues (5-10) of eudistidine C. Chiral-phase HPLC resolution of epimeric eudistidine C provided (+)-(R)-eudistidine C (1a) and (-)-(S)-eudistidine C (1b). The absolute configuration of these enantiomers was assigned by ECD analysis. (-)-(S)-Eudistidine C (1b) modestly inhibited interaction between the protein binding domains of HIF-1α and p300. Compounds 1, 2, and 6-10 exhibited significant antimalarial activity against Plasmodium falciparum.

Jamaicensamide A, a Peptide Containing β-Amino-α-keto and Thiazole-Homologated η-Amino Acid Residues from the Sponge Plakina jamaicensis

A new cyclic peptide, jamaicensamide A, composed of six amino acids, including a thiazole-homologated amino acid, was isolated from the Bahamian sponge Plakina jamaicensis, along with known compounds bitungolide A and franklinolide A. The structure of the title peptide was solved by integrated analysis of MS, 1D and 2D NMR data, oxidation-hydrolyses to α-amino acids, and their stereodetermination by Marfey's method. The close structural resemblance of Western Atlantic-derived jamaicensamide A to known Western Pacific-derived peptides of lithistid sponges in the genus Theonella and Discodermia suggests a common origin: the symbiotic bacterium Entotheonella sp., a so-called "talented producer" responsible for biosynthesis of most Theonella-associated peptides. Similar natural products from sponges of disparate genera evince the likelihood that these invertebrates harbor the same or a very similar symbiont.

The fundamentals behind solving for unknown molecular structures using computer-assisted structure elucidation: a free software package at the undergraduate and graduate levels

The successful elucidation of an unknown compound's molecular structure often requires an analyst with profound knowledge and experience of advanced spectroscopic techniques, such as Nuclear Magnetic Resonance (NMR) spectroscopy and mass spectrometry. The implementation of Computer-Assisted Structure Elucidation (CASE) software in solving for unknown structures, such as isolated natural products and/or reaction impurities, can serve both as elucidation and teaching tools. As such, the introduction of CASE software with 112 exercises to train students in conjunction with the traditional pen and paper approach will strengthen their overall understanding of solving unknowns and explore of various structural end points to determine the validity of the results quickly. Copyright © 2016 John Wiley & Sons, Ltd.

Metabolomics in rheumatic diseases: desperately seeking biomarkers

Metabolomics enables the profiling of large numbers of small molecules in cells, tissues and biological fluids. These molecules, which include amino acids, carbohydrates, lipids, nucleotides and their metabolites, can be detected quantitatively. Metabolomic methods, often focused on the information-rich analytical techniques of NMR spectroscopy and mass spectrometry, have potential for early diagnosis, monitoring therapy and defining disease pathogenesis in many therapeutic areas, including rheumatic diseases. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanisms are being revealed and are shaping our understanding of cell biology, physiology and medicine. These pathways can potentially be targeted to diagnose and treat patients with immune-mediated diseases.

Xanthones of Lichen Source: A 2016 Update

An update of xanthones encountered in lichens is proposed as more than 20 new xanthones have been described since the publication of the compendium of lichen metabolites by Huneck and Yoshimura in 1996. The last decades witnessed major advances regarding the elucidation of biosynthetic schemes leading to these fascinating compounds, accounting for the unique substitution patterns of a very vast majority of lichen xanthones. Besides a comprehensive analysis of the structures of xanthones described in lichens, their bioactivities and the emerging analytical strategies used to pinpoint them within lichens are presented here together with physico-chemical properties (including NMR data) as reported since 1996.