Bioactivity-Based Molecular Networking for the Discovery of Drug Leads in Natural Product Bioassay-Guided Fractionation

A Fast and Efficient Molecular Networking Approach for Reactivity of Natural Products Exploration in Plant Extracts: Application to Diterpene Esters from Euphorbia dendroides

Natural products represent a rich source of bioactive compounds, covering a large chemical space. Even if challenging, this diversity can be extended by applying chemical modifications. However, these studies generally require multigram amounts of isolated natural products and face frequent testing failures. To overcome this limitation, we propose a rapid and efficient approach that uses molecular networking (MN) to visualize the new chemical diversity generated by simple chemical modifications of natural extracts. Moreover, the strategy deployed enables the most appropriate reagents to be defined quickly upstream of a reaction on a pure compound, in order to maximize chemical diversity. This methodology was applied to the latex extract of Euphorbia dendroides to follow the reactivity toward a series of Brønsted and Lewis acids of three class of diterpene esters identified in this species: jatrophane, terracinolide, and phorbol. Through the molecular networking interpretation, with the aim to illustrate our approach, BF3·OEt2 was selected for chemical modification on isolated jatrophane esters. Three rearranged compounds (3-5) were obtained, showing that the most appropriate reagents can be selected by MN interpretation.

Bioactivity-Based Molecular Networking-Guided Isolation of Epicolidines A-C from the Endophytic Fungus Epicoccum sp. 1-042

Bioactivity-based molecular networking-guided fractionation enabled the isolation of three new polycyclic tetramic acids bearing cis-decalin, epicolidines A-C (1-3), along with one known compound, PF 1052 (4), from the endophytic fungus Epicoccum sp. 1-042 collected in Tibet, China. Their structures were assigned on the basis of extensive spectroscopic data, partial hydrolysis, advanced Marfey's method, quantum chemistry calculations, and X-ray diffraction analysis. Compounds 2-4 displayed promising activities against Gram-positive bacteria in vitro. Particularly, compound 4 displayed remarkable potential against vancomycin-resistant Enterococcus faecium (VRE) with an MIC value of 0.25 μg/mL, lower than the MIC (0.5 μg/mL) of the antibiotic combination quinupristin/dalfopristin (Q/D). In a further in vivo study, compound 4 increased the survival rate to 100% in the VRE-G. mellonella infection model at a concentration of 10 mg/kg.

Escuzarmycins A-D, Potent Biofungicides to Control Septoria tritici Blotch

A study targeting novel antifungal metabolites identified potent in vitro antifungal activity against key plant pathogens in acetone extracts of Streptomyces sp. strain CA-296093. Feature-based molecular networking revealed the presence in this extract of antimycin-related compounds, leading to the isolation of four new compounds: escuzarmycins A-D (1-4). Extensive structural elucidation, employing 1D and 2D NMR, high-resolution mass spectrometry, Marfey's analysis, and NOESY correlations, confirmed their structures. The bioactivity of these compounds was tested against six fungal phytopathogens, and compounds 3 and 4 demonstrated strong efficacy, particularly against Zymoseptoria tritici, with compound 3 exhibiting the highest potency (EC50: 11 nM). Both compounds also displayed significant antifungal activity against Botrytis cinerea and Colletotrichum acutatum, with compound 4 proving to be the most potent. Despite moderate cytotoxicity against the human cancer cell line HepG2, compounds 3 and 4 emerge as promising fungicides for combating Septoria tritici blotch, anthracnose, and gray mold.

Connecting metabolome and phenotype: recent advances in functional metabolomics tools for the identification of bioactive natural products

Covering: 1995 to 2023Advances in bioanalytical methods, particularly mass spectrometry, have provided valuable molecular insights into the mechanisms of life. Non-targeted metabolomics aims to detect and (relatively) quantify all observable small molecules present in a biological system. By comparing small molecule abundances between different conditions or timepoints in a biological system, researchers can generate new hypotheses and begin to understand causes of observed phenotypes. Functional metabolomics aims to investigate the functional roles of metabolites at the scale of the metabolome. However, most functional metabolomics studies rely on indirect measurements and correlation analyses, which leads to ambiguity in the precise definition of functional metabolomics. In contrast, the field of natural products has a history of identifying the structures and bioactivities of primary and specialized metabolites. Here, we propose to expand and reframe functional metabolomics by integrating concepts from the fields of natural products and chemical biology. We highlight emerging functional metabolomics approaches that shift the focus from correlation to physical interactions, and we discuss how this allows researchers to uncover causal relationships between molecules and phenotypes.

Mirror, mirror on the wall, which phytochemicals in Clinacanthus nutans inhibits advanced glycation end products of them all?

In our quest to discover advanced glycation end products (AGEs) inhibitors from Clinacanthus nutans (Burm.f.) Lindau leaves, we conducted a bioactivity-based molecular networking. This approach integrates LC-MS2 profiling and in vitro antiglycation data to predict bioactive compounds. We began by screening three extracts: 100% ethanol, 70% ethanol and 100% water alongside the in vitro antioxidant activity, total phenolics content (TPC) and schaftoside content. Among these extracts, 100% ethanol extract exhibited the highest total AGEs inhibition effects (IC50 = 80.18 ± 11.6 μg/mL), DPPH scavenging activity (IC50 = 747.40 ± 10.30 μg/mL) and TPC (26.54 ± 2.09 μg GAE /mg extract). Intriguingly, 100% ethanol extract contained the lowest amount of schaftoside, suggesting the involvement of other phytochemicals in the antiglycation effects. The molecular networking and in silico structural annotations of 401 LC-MS features detected in the fractions from 100% ethanol extract predicted 21 bioactive compounds (p < 0.05, r > 0.90), including several C40 carotenoids, alkaloids containing tetrapyrrole structures and fatty acids. On the contrary, all phenolics showed weak correlations with antiglycation effects. These predictions were further validated in vitro, where carotenoid lutein showed half maximal inhibitory concentration, IC50 = 96 ± 8 μM and selected flavonoid-C-glycosides exhibited weaker inhibitions (IC50 between 568 and 1922 μM). Notably, lutein content was higher in freeze-dried leaves (12.42 ± 0.82 mg/100 g) than oven-dried, although the former was associated with elevated mercury levels. In summary, C. nutans exhibited potential antiglycation and antioxidant activity, and lutein was identified as the main bioactive principle.

Plant antibacterials: The challenges and opportunities

Nature possesses an inexhaustible reservoir of agents that could serve as alternatives to combat the growing threat of antimicrobial resistance (AMR). While some of the most effective drugs for treating bacterial infections originate from natural sources, they have predominantly been derived from fungal and bacterial species. However, a substantial body of literature is available on the promising antibacterial properties of plant-derived compounds. In this comprehensive review, we address the major challenges associated with the discovery and development of plant-derived antimicrobial compounds, which have acted as obstacles preventing their clinical use. These challenges encompass limited sourcing, the risk of agent rediscovery, suboptimal drug metabolism, and pharmacokinetics (DMPK) properties, as well as a lack of knowledge regarding molecular targets and mechanisms of action, among other pertinent issues. Our review underscores the significance of these challenges and their implications in the quest for the discovery and development of effective plant-derived antimicrobial agents. Through a critical examination of the current state of research, we give valuable insights that will advance our understanding of these classes of compounds, offering potential solutions to the global crisis of AMR. © 2017 Elsevier Inc. All rights reserved.

Rationally Minimizing Natural Product Libraries Using Mass Spectrometry

Natural product libraries are crucial to drug development, but large libraries drastically increase the time and cost during initial high throughput screens. Here, we developed a method that leverages liquid chromatography-tandem mass spectrometry spectral similarity to dramatically reduce library size, with minimal bioactive loss. This method offers a broadly applicable strategy for accelerated drug discovery with cost reductions, which enable implementation in resource-limited settings.

Charting the Cannabis plant chemical space with computational metabolomics

INTRODUCTION

The chemical classification of Cannabis is typically confined to the cannabinoid content, whilst Cannabis encompasses diverse chemical classes that vary in abundance among all its varieties. Hence, neglecting other chemical classes within Cannabis strains results in a restricted and biased comprehension of elements that may contribute to chemical intricacy and the resultant medicinal qualities of the plant.

OBJECTIVES

Thus, herein, we report a computational metabolomics study to elucidate the Cannabis metabolic map beyond the cannabinoids.

METHODS

Mass spectrometry-based computational tools were used to mine and evaluate the methanolic leaf and flower extracts of two Cannabis cultivars: Amnesia haze (AMNH) and Royal dutch cheese (RDC).

RESULTS

The results revealed the presence of different chemical compound classes including cannabinoids, but extending it to flavonoids and phospholipids at varying distributions across the cultivar plant tissues, where the phenylpropnoid superclass was more abundant in the leaves than in the flowers. Therefore, the two cultivars were differentiated based on the overall chemical content of their plant tissues where AMNH was observed to be more dominant in the flavonoid content while RDC was more dominant in the lipid-like molecules. Additionally, in silico molecular docking studies in combination with biological assay studies indicated the potentially differing anti-cancer properties of the two cultivars resulting from the elucidated chemical profiles.

CONCLUSION

These findings highlight distinctive chemical profiles beyond cannabinoids in Cannabis strains. This novel mapping of the metabolomic landscape of Cannabis provides actionable insights into plant biochemistry and justifies selecting certain varieties for medicinal use.

B. Trivella D. NP3 MS Workflow: An Open-Source Software System to Empower Natural Product-Based Drug Discovery Using Untargeted Metabolomics

Natural products (or specialized metabolites) are historically the main source of new drugs. However, the current drug discovery pipelines require miniaturization and speeds that are incompatible with traditional natural product research methods, especially in the early stages of the research. This article introduces the NP3 MS Workflow, a robust open-source software system for liquid chromatography-tandem mass spectrometry (LC-MS/MS) untargeted metabolomic data processing and analysis, designed to rank bioactive natural products directly from complex mixtures of compounds, such as bioactive biota samples. NP3 MS Workflow allows minimal user intervention as well as customization of each step of LC-MS/MS data processing, with diagnostic statistics to allow interpretation and optimization of LC-MS/MS data processing by the user. NP3 MS Workflow adds improved computing of the MS2 spectra in an LC-MS/MS data set and provides tools for automatic [M + H]+ ion deconvolution using fragmentation rules; chemical structural annotation against MS2 databases; and relative quantification of the precursor ions for bioactivity correlation scoring. The software will be presented with case studies and comparisons with equivalent tools currently available. NP3 MS Workflow shows a robust and useful approach to select bioactive natural products from complex mixtures, improving the set of tools available for untargeted metabolomics. It can be easily integrated into natural product-based drug-discovery pipelines and to other fields of research at the interface of chemistry and biology.

Naturally Occurring Norsteroids and Their Design and Pharmaceutical Application

The main focus of this review is to introduce readers to the fascinating class of lipid molecules known as norsteroids, exploring their distribution across various biotopes and their biological activities. The review provides an in-depth analysis of various modified steroids, including A, B, C, and D-norsteroids, each characterized by distinct structural alterations. These modifications, which range from the removal of specific methyl groups to changes in the steroid core, result in unique molecular architectures that significantly impact their biological activity and therapeutic potential. The discussion on A, B, C, and D-norsteroids sheds light on their unique configurations and how these structural modifications influence their pharmacological properties. The review also presents examples from natural sources that produce a diverse array of steroids with distinct structures, including the aforementioned A, B, C, and D-nor variants. These compounds are sourced from marine organisms like sponges, soft corals, and starfish, as well as terrestrial entities such as plants, fungi, and bacteria. The exploration of these steroids encompasses their biosynthesis, ecological significance, and potential medical applications, highlighting a crucial area of interest in pharmacology and natural product chemistry. The review emphasizes the importance of researching these steroids for drug development, particularly in addressing diseases where conventional medications are inadequate or for conditions lacking sufficient therapeutic options. Examples of norsteroid synthesis are provided to illustrate the practical applications of this research.

Targeting of Antifungal Metabolites from Grapevine Byproducts by UPLC-HRMS/MS Approaches Using Bioactivity-Based Molecular Networking

This study focuses on countering Fusarium graminearum, a harmful fungal pathogen impacting cereal crops and human health through mycotoxin production. These mycotoxins, categorized as type B trichothecenes, pose significant health risks. Research explores natural alternatives to synthetic fungicides, particularly investigating phenolics in grapevine byproducts. Thirteen eco-extracts from five French grape varieties (Merlot, Cabernet Sauvignon, Sauvignon blanc, Tannat, and Artaban) exhibited substantial antifungal properties, with ten extracts displaying remarkable effects. Extracts from grapevine stems and roots notably reduced fungal growth by over 91% after five days. Through UHPLC-HRMS/MS analysis and metabolomics, the study identified potent antifungal compounds such as ampelopsin A and cyphostemmin B, among other oligomeric stilbenes. Interestingly, this approach showed that flavan-3-ols have been identified as markers for extracts that induce fungal growth. Root extracts from rootstocks, rich in oligostilbenes, demonstrated the highest antifungal activity. This research underscores grapevine byproducts' potential both as a sustainable approach to control F. graminearum and mycotoxin contamination in cereal crops and the presence of different metabolites from the cultivars of grapevine, suggesting different activities.

Tailored Mass Spectral Data Exploration Using the SpecXplore Interactive Dashboard

Untargeted metabolomics promises comprehensive characterization of small molecules in biological samples. However, the field is hampered by low annotation rates and abstract spectral data. Despite recent advances in computational metabolomics, manual annotations and manual confirmation of in-silico annotations remain important in the field. Here, exploratory data analysis methods for mass spectral data provide overviews, prioritization, and structural hypothesis starting points to researchers facing large quantities of spectral data. In this research, we propose a fluid means of dealing with mass spectral data using specXplore, an interactive Python dashboard providing interactive and complementary visualizations facilitating mass spectral similarity matrix exploration. Specifically, specXplore provides a two-dimensional t-distributed stochastic neighbor embedding embedding as a jumping board for local connectivity exploration using complementary interactive visualizations in the form of partial network drawings, similarity heatmaps, and fragmentation overview maps. SpecXplore makes use of state-of-the-art ms2deepscore pairwise spectral similarities as a quantitative backbone while allowing fast changes of threshold and connectivity limitation settings, providing flexibility in adjusting settings to suit the localized node environment being explored. We believe that specXplore can become an integral part of mass spectral data exploration efforts and assist users in the generation of structural hypotheses for compounds of interest.

Theoretical framework to evaluate antioxidant synergistic effects from the coextraction of marjoram, rosemary and parsley

Synergies between compounds in food ingredients have been commonly obtained by the mixing of extracts produced individually. A different approach, based on the coextraction of plants and a new theoretical framework to identify synergistic and antagonistic effects in the coextracts, has been proposed in this study for the first time. The Pressurized Liquid Extraction (PLE) of rosemary and marjoram with parsley at several plant ratios was carried out and the antioxidant activity (ABTS and cellular assays) and phenolic compounds of the extracts were evaluated. Synergistic effects on the antioxidant activity of the extracts were identified from all the plant combinations. The HPLC-PAD analysis of the samples did not show a relation between the concentration of the main phenolic compounds in the coextracts and the observed antioxidant synergistic effects. The proposed theoretical framework may be successfully used for the determination of synergies in the bioactivity of extracts obtained by coextraction.

Licorice extract inhibits porcine epidemic diarrhea virus in vitro and in vivo

Porcine epidemic diarrhea virus (PEDV) causes severe diarrhea and even death in piglets, resulting in significant economic losses to the pig industry. Because of the ongoing mutation of PEDV, there might be variations between the vaccine strain and the prevailing strain, causing the vaccine to not offer full protection against different PEDV variant strains. Therefore, it is necessary to develop anti-PEDV drugs to compensate for vaccines. This study confirmed the anti-PEDV effect of licorice extract (Le) in vitro and in vivo. Le inhibited PEDV replication in a dose-dependent manner in vitro. By exploring the effect of Le on the life cycle of PEDV, we found that Le inhibited the attachment, internalization, and replication stages of the virus. In vivo, all five piglets in the PEDV-infected group died within 72 h. In comparison, the Le-treated group had a survival rate of 80 % at the same time, with significant relief of clinical symptoms, pathological damage, and viral loads in the jejunum and ileum. Our results suggested that Le can exert anti-PEDV effects in vitro and in vivo. Le is effective and inexpensive; therefore it has the potential to be developed as a new anti-PEDV drug.

A guide to the use of bioassays in exploration of natural resources

Bioassays are the main tool to decipher bioactivities from natural resources thus their selection and quality are critical for optimal bioprospecting. They are used both in the early stages of compounds isolation/purification/identification, and in later stages to evaluate their safety and efficacy. In this review, we provide a comprehensive overview of the most common bioassays used in the discovery and development of new bioactive compounds with a focus on marine bioresources. We present a comprehensive list of practical considerations for selecting appropriate bioassays and discuss in detail the bioassays typically used to explore antimicrobial, antibiofilm, cytotoxic, antiviral, antioxidant, and anti-ageing potential. The concept of quality control and bioassay validation are introduced, followed by safety considerations, which are critical to advancing bioactive compounds to a higher stage of development. We conclude by providing an application-oriented view focused on the development of pharmaceuticals, food supplements, and cosmetics, the industrial pipelines where currently known marine natural products hold most potential. We highlight the importance of gaining reliable bioassay results, as these serve as a starting point for application-based development and further testing, as well as for consideration by regulatory authorities.

Plant peptides - redefining an area of ribosomally synthesized and post-translationally modified peptides

Covering 1965 to February 2024Plants are prolific peptide chemists and are known to make thousands of different peptidic molecules. These peptides vary dramatically in their size, chemistry, and bioactivity. Despite their differences, all plant peptides to date are biosynthesized as ribosomally synthesized and post-translationally modified peptides (RiPPs). Decades of research in plant RiPP biosynthesis have extended the definition and scope of RiPPs from microbial sources, establishing paradigms and discovering new families of biosynthetic enzymes. The discovery and elucidation of plant peptide pathways is challenging due to repurposing and evolution of housekeeping genes as both precursor peptides and biosynthetic enzymes and due to the low rates of gene clustering in plants. In this review, we highlight the chemistry, biosynthesis, and function of the known RiPP classes from plants and recommend a nomenclature for the recent addition of BURP-domain-derived RiPPs termed burpitides. Burpitides are an emerging family of cyclic plant RiPPs characterized by macrocyclic crosslinks between tyrosine or tryptophan side chains and other amino acid side chains or their peptide backbone that are formed by copper-dependent BURP-domain-containing proteins termed burpitide cyclases. Finally, we review the discovery of plant RiPPs through bioactivity-guided, structure-guided, and gene-guided approaches.

Integrating High-Resolution Mass Spectral Data, Bioassays and Computational Models to Annotate Bioactives in Botanical Extracts: Case Study Analysis of C. asiatica Extract Associates Dicaffeoylquinic Acids with Protection against Amyloid-β Toxicity

Rapid screening of botanical extracts for the discovery of bioactive natural products was performed using a fractionation approach in conjunction with flow-injection high-resolution mass spectrometry for obtaining chemical fingerprints of each fraction, enabling the correlation of the relative abundance of molecular features (representing individual phytochemicals) with the read-outs of bioassays. We applied this strategy for discovering and identifying constituents of Centella asiatica (C. asiatica) that protect against Aβ cytotoxicity in vitro. C. asiatica has been associated with improving mental health and cognitive function, with potential use in Alzheimer's disease. Human neuroblastoma MC65 cells were exposed to subfractions of an aqueous extract of C. asiatica to evaluate the protective benefit derived from these subfractions against amyloid β-cytotoxicity. The % viability score of the cells exposed to each subfraction was used in conjunction with the intensity of the molecular features in two computational models, namely Elastic Net and selectivity ratio, to determine the relationship of the peak intensity of molecular features with % viability. Finally, the correlation of mass spectral features with MC65 protection and their abundance in different sub-fractions were visualized using GNPS molecular networking. Both computational methods unequivocally identified dicaffeoylquinic acids as providing strong protection against Aβ-toxicity in MC65 cells, in agreement with the protective effects observed for these compounds in previous preclinical model studies.

Molecular networking unveils anti-SARS-CoV-2 constituents from traditionally used remedies

ETHNOPHARMACOLOGICAL RELEVANCE

Plants and fungi have a long tradition in ethnopharmacology for the treatment of infectious diseases including viruses. Many of these natural products have also been used to combat SARS-CoV-2 infections or symptoms of the post- and long-COVID form, owing to the scarcity of clinically approved therapeutics.

AIM OF THE STUDY

The ongoing threat posed by SARS-CoV-2, along with the rapidly evolving new variants, requires the development of new antiviral compounds. The aim of this study was to identify anti-SARS-CoV-2 herbal and fungal extracts used in traditional medicine against acute respiratory infection, inflammation, and related symptoms. Additionally, we sought to characterize their bioactive constituents.

MATERIALS AND METHODS

The antiviral activity and cell cytotoxicity of 179 herbal and fungal extracts were evaluated using two SARS-CoV-2 infection assays in Caco-2 cells. 19 plant extracts with and without anti-SARS-CoV-2 activity underwent detailed dereplication using molecular networking.

RESULTS

Extracts from Angelica sinensis (Oliv.) Diels roots, Annona squamosa L. seeds, Azadirachta indica A. Juss. fruits, Buddleja officinalis Maxim. flowers, Burkea africana Hook. bark and Clinopodium menthifolium (Host) Stace aerial parts showed a potent anti SARS-CoV-2 activity (IC50 < 5 μg/ml) with only moderate cytotoxicity (CC50 > 60 μg/ml, Caco-2). By performing the dereplication with a bioactivity-featured molecular network (MN) on the extract library level, rather than on the level of individual extracts, we could pinpoint compounds characteristic for active extracts. Thus, a straight-forward identification of potential anti-SARS-CoV-2 natural compounds was achieved prior to any fractionation or isolation efforts.

CONCLUSIONS

A sophisticated hyphenation of empirical knowledge with MS-based bioinformatics and automated compound annotation was applied to decipher the chemical space of the investigated extracts. The correlation with experimentally assessed anti-SARS-CoV-2 activities helped in predicting compound classes and structural elements relevant for the antiviral activities. Consequently, this accelerated the identification of constituents from the investigated mixtures with inhibitory effects against SARS-CoV-2.

Dipeniroqueforins A-B and Peniroqueforin D: Eremophilane-Type Sesquiterpenoid Derivatives with Cytotoxic Activity from Penicillium roqueforti

Guided by the Global Natural Products Social (GNPS) molecular networking strategy, five undescribed eremophilane-type sesquiterpenoid derivatives (1-5) were isolated and identified from fungus Penicillium roqueforti, which was separated from the root soil of plant Hypericum beanii collected in Shennongjia Forestry District, Hubei Province. Dipeniroqueforins A-B (1-2), representing a lactam-type sesquiterpenoid skeleton with a highly symmetrical and homodimeric 5/6/6-6/6/5 hexacyclic system, are reported within the eremophilane-type family for the first time. Peniroqueforin D (5) represents the first example of a 1,2-seco eremophilane-type sesquiterpenoid derivative featuring an undescribed 7/6-fused ring system. The structures of these compounds were elucidated by various spectroscopic analyses, DP4+ probability analyses, ECD calculations, and single-crystal X-ray diffraction experiments. Furthermore, these isolates were evaluated for cytotoxicity, and the result uncovered that compound 1 displayed broad-spectrum activity. Further mechanistic study revealed that compound 1 could significantly upregulate the mRNA expression of genes related to the oxidative induction, leading to the abnormal ROS levels in tumor cells and ultimately causing tumor cell apoptosis.

Bifidobacterium alleviate metabolic disorders via converting methionine to 5'-methylthioadenosine

Dietary patterns and corresponding gut microbiota profiles are associated with various health conditions. A diet rich in polyphenols, primarily plant-based, has been shown to promote the growth of probiotic bacteria in the gastrointestinal tract, subsequently reducing the risk of metabolic disorders in the host. The beneficial effects of these bacteria are largely due to the specific metabolites they produce, such as short-chain fatty acids and membrane proteins. In this study, we employed a metabolomics-guided bioactive metabolite identification platform that included bioactivity testing using in vitro and in vivo assays to discover a bioactive metabolite produced from probiotic bacteria. Through this approach, we identified 5'-methylthioadenosine (MTA) as a probiotic bacterial-derived metabolite with anti-obesity properties. Furthermore, our findings indicate that MTA administration has several regulatory impacts on liver functions, including modulating fatty acid synthesis and glucose metabolism. The present study elucidates the intricate interplay between dietary habits, gut microbiota, and their resultant metabolites.

High-speed countercurrent chromatography with offline detection by electrospray mass spectrometry and nuclear magnetic resonance detection as a tool to resolve complex mixtures: A practical approach using Coffea arabica leaf extract

INTRODUCTION

Many secondary metabolites isolated from plants have been described in the literature owing to their important biological properties and possible pharmacological applications. However, the identification of compounds present in complex plant extracts has remained a great scientific challenge, is often laborious, and requires a long research time with high financial cost.

OBJECTIVES

The aim of this study was to develop a method that allows the identification of secondary metabolites in plant extracts with a high degree of confidence in a short period of time.

MATERIAL AND METHODS

In this study, an ethanolic extract of Coffea arabica leaves was used to validate the proposed method. Countercurrent chromatography was chosen as the initial step for extraction fractionation using gradient elution. Resulting fractions presented a variation of compounds concentrations, allowing for statistical total correlation spectroscopy (STOCSY) calculations between liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS/MS) and NMR across fractions.

RESULTS

The proposed method allowed the identification of 57 compounds. Of the annotated compounds, 20 were previously described in the literature for the species and 37 were reported for the first time. Among the inedited compounds, we identified flavonoids, alkaloids, phenolic acids, coumarins, and terpenes.

CONCLUSION

The proposed method presents itself as a valid alternative for the study of complex extracts in an effective, fast, and reliable way that can be reproduced in the study of other extracts.

Marmesin isolated from Celtis durandii Engl. root bioactive fraction inhibits β-hematin formation and contributes to antiplasmodial activity

ETHNOPHARMACOLOGICAL RELEVANCE

Malaria is a leading cause of death in many developing countries, especially in sub-Saharan Africa. Nigeria is endowed with an abundance of medicinal plants, many of which are used to treat malaria. Celtis durandii Engl. is one such plant used as a traditional antimalarial remedy in southeast Nigeria. However, its antiplasmodial potential is poorly explored.

AIM OF THE STUDY

The study aimed at identifying the antiplasmodial components of C. durandii root extract through antiplasmodial activity-guided fractionation.

MATERIALS AND METHODS

Dichloromethane/methanol mixture extract (1:1 v/v) of C. durandii root was prepared and partitioned against water to obtain the organic phase, which was further separated by column chromatography into nine (C1 - C9) fractions. The antiplasmodial activity was evaluated by in vitro screening of the different fractions against drug-sensitive and drug-resistant Plasmodium falciparum strains. Further purification of the active column fractions resulted in a potent anti-Plasmodial compound that was subsequently investigated for its effect on β-hematin formation. Additionally, the isolated compound was characterized and identified as marmesin using mass spectrometry and nuclear magnetic resonance spectroscopy.

RESULTS

Celtis durandii root extract exhibited promising antiplasmodial activity {IC50 (μg/ml) 5.92, 6.04, and 6.92} against PfW2mef, PfINDO, and Pf3D7 respectively. Pooled fractions with good antiplasmodial activity {IC50 (μg/ml) Pf3D7: 3.99; PfINDO: 2.24} and selectivity for the parasites (SI: 21) yielded a compound that was fourteen-fold potent in antiplasmodial activity against Pf3D7(IC50: 0.28 μg/ml). It also inhibited β-hematin formation with an IC50 = 150 μM. Further studies using spectral data, literature, and chemical databases identified the purified compound as marmesin.

CONCLUSION

This work has demonstrated that Celtis durandii root extract has good antiplasmodial activity against drug-sensitive and drug-resistant P. falciparum. The inhibition of β-hematin formation by marmesin accounts in part for this activity.

Progress and challenges in exploring aquatic microbial communities using non-targeted metabolomics

Advances in bioanalytical technologies are constantly expanding our insights into complex ecosystems. Here, we highlight strategies and applications that make use of non-targeted metabolomics methods in aquatic chemical ecology research and discuss opportunities and remaining challenges of mass spectrometry-based methods to broaden our understanding of environmental systems.

Characterization of Brazilian green propolis as a photosensitizer for LED light-induced antimicrobial photodynamic therapy (aPDT) against methicillin-resistant Staphylococcus aureus (MRSA) and Vancomycin-intermediate Staphylococcus aureus (VISA)

Staphylococcus aureus is the primary cause of skin and soft tissue infections. Its significant adaptability and the development of resistance are the main factors linked to its spread and the challenges in its treatment. Antimicrobial photodynamic therapy emerges as a promising alternative. This work aimed to characterize the antimicrobial photodynamic activity of Brazilian green propolis, along with the key bioactive compounds associated with this activity. Initially, a scanning spectrometry was conducted to assess the wavelengths with the potential to activate green propolis. Subsequently, reference strains of methicillin-resistant Staphylococcus aureus (MRSA ATCC 43300) and vancomycin-intermediate Staphylococcus aureus (VISA ATCC 700699) were exposed to varying concentrations of green propolis: 1 µg/mL, 5 µg/mL, 10 µg/mL, 50 µg /mL and 100 µg/mL and were stimulated by blue, green or red LED light. Finally, high-performance liquid chromatography coupled with a diode array detector and tandem mass spectrometry techniques, along with classic molecular networking analysis, was performed to identify potential bioactive molecules with photodynamic activity. Brazilian green propolis exhibits a pronounced absorption peak and heightened photo-responsiveness when exposed to blue light within the range of 400 nm and 450 nm. This characteristic reveals noteworthy significant photodynamic activity against MRSA and VISA at concentrations from 5 µg/mL. Furthermore, the propolis comprises compounds like curcumin and other flavonoids sourced from flavone, which possess the potential for photodynamic activity and other antimicrobial functions. Consequently, Brazilian green propolis holds promise as an excellent bactericidal agent, displaying a synergistic antibacterial property enhanced by light-induced photodynamic effects.

Subplenones A-J: Dimeric Xanthones with Antibacterial Activity from the Endophytic Fungus Subplenodomus sp. CPCC 401465

Subplenones A-J (1-10), 10 new xanthone dimers, have been isolated and characterized from the endophytic fungus Subplenodomus sp. CPCC 401465, which resides within the Chinese medicinal plant Gentiana straminea. The isolation process was guided by antibacterial assays and molecular-networking-based analyses. The chemical structures of these compounds were elucidated through the interpretation of nuclear magnetic resonance (NMR) and high-resolution electrospray ionization mass spectrometry (HRESIMS) data. Furthermore, the relative configuration of the compounds was determined using NMR and single-crystal X-ray diffraction analyses, and the absolute configuration was established using electronic circular dichroism calculations. All of the isolated compounds exhibited significant inhibitory activity against Gram-positive bacteria. Notably, compounds 1, 5, and 7 displayed remarkable inhibitory activity against methicillin-resistant Staphylococcus aureus (MRSA) ATCC 700698, with a minimum inhibitory concentration (MIC) of 0.25 μg/mL, and against vancomycin-resistant Enterococcus faecium (VRE) ATCC 700221, with MIC values ranging from 0.5 to 1.0 μg/mL.

Activity labelled molecular networking fuels the antioxidation active molecules profile of Ginger

Ginger has been used as consumed food spice and folk medicine in daily life for thousands of years in various regions of the world. Considerable antioxidation is one of the major activities for Ginger to exhibit health-promoting effects. In this study, a bioinformatic workflow was developed to generate activity labelled molecular networking (ALMN) to fuel the antioxidation active molecules profile of Ginger. In ALMN, antioxidation activity data, which was defined as correlation (r and p value) between the relative abundance of a molecule in fractions and the activity level of each fraction, was labelled to feature-based molecular network to profile out antioxidation active molecules visually. Fragmentation tree was further computed as a complementary way to conduct high confidence structure annotations of antioxidation active molecules. Consequently, 48 molecules were prioritized as antioxidation active molecules from 11,720 metabolite molecules of Ginger in a systematical way.

Marine indole alkaloid diversity and bioactivity. What do we know and what are we missing?

Covering: marine indole alkaloids (n = 2048) and their reported bioactivities up to the end of 2021Despite increasing numbers of marine natural products (MNPs) reported each year, most have only been examined for cytotoxic, antibacterial, and/or antifungal biological activities with the majority found to be inactive in these assays. In this context, why are natural products continuing to be examined in assays they are unlikely to show significant activity in, and what targets might be more useful for expanding knowledge of their biologically relevant chemical space? We have undertaken a meta-analysis of the biological activities for 2048 marine indole alkaloids (MIAs), a diverse sub-class of MNPs reported up to the end of 2021, and this has highlighted that the bioactivity potentials for up to 86% of published MIAs remains underexplored and/or undefined. Although most published MIAs are not cytotoxic or antimicrobial, there is a continued focus on using these assays to evaluate new structurally related analogues. Using cheminformatics analyses, the chemical diversity of the 2048 MIAs were clustered using fragment based fingerprints and their reported bioactivity potency towards specific disease targets was assessed for structure activity trends. These analyses showed that there are groups of MIAs that possess potent and diverse activities and that many analogues, previously tested only in cellular toxicity assays, could be better exploited to generate structure activity relationships associated with leads to treat emerging diseases. A collection of indole drug and drug-lead structures from non-natural sources were also incorporated into the dataset providing complementary bioactivity profiles that were further used to predict underexplored areas of potential new activity and to better direct future testing of MIAs. Our findings clearly suggest the biological evaluation of MIAs continues to be conducted on a narrow range of bioassays and disease targets, and that shifting the focus to non-toxic disease targets should provide expanded knowledge of biologically relevant chemical space aimed at maximising the potential of MIAs for drug discovery.

Seasonal variation in the metabolome expression of Jania rubens (Rhodophyta) reveals eicosapentaenoic acid as a potential anticancer metabolite

Seaweeds of the intertidal zone are subjected to diverse stresses due to environmental changes in radiation, salinity, water quality, herbivore communities, etc. Thus, marine seaweeds developed various unique compounds to deal with environmental fluctuations. Therefore, they are a good source of unique novel compounds. Here, we explored the seasonal metabolomic changes in Jania rubens and found notable changes between extracts of different seasons in the metabolomic profile and in their anticancer activity. The most bioactive extract was from samples collected during the Fall season, which demonstrated an LC50 of 178.39 (± 10.02 SD) µg/ml toward Non Small Cell Lung Cancer (NSCLC) followed by the Winter season extract. The Fall and Winter extracts also displayed more resemblance in their metabolic profile relative to Spring and Summer extracts. The Fall extract was fractionated and tested for cytotoxic activity toward an array of cancer cell lines. Eventually, using a bio-guided assay and multiple fractionation steps, we isolated and identified the essential fatty acid, eicosapentaenoic acid, as the active anticancer agent, showing an LC50 of 5.23 (± 0.07 SD) µg/ml toward NSCLC. Our results emphasize the potential use of J. rubens as a source of beneficial fatty acids and stress the importance of environmental effects on metabolic constitutes.

Rationalising the retro-Diels-Alder fragmentation pattern of viscutins using electrospray interface-tandem mass spectrometry coupled to theoretical modelling

RATIONALE

Although mass spectrometry (MS) is a powerful tool in structural elucidation of unknown flavonoids based on their unique fragmentation patterns, proposing the correct fragmentation mechanism is still a challenge from tandem mass spectrometry data only. In recent years, computational tools such as molecular networking and MS2LDA have played a major role in the identification of structurally related compounds through an in-depth survey of their fragmentation patterns.

METHODS

Therefore, in this study, three viscutin molecules in Viscum combreticola Engl. crude extracts were characterised using ultra-high-performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry and MS2LDA, a computational tool. Ion-trap mass spectrometry and density functional theoretical modelling were used as confirmatory tools to rationalise the unique fragmentation patterns observed for these molecules.

RESULTS

Here, MS2LDA revealed the presence of a unique Mass2Motif in all the three viscutin molecules at m/z 137, which was confirmed to be a ^1,3 A^- RDA (retro-Diels-Alder) fragmentation product using liquid chromatography-ion-trap mass spectrometry and density functional theoretical modelling. Moreover, MS2LDA proved to be useful in differentiating this spectral feature that was specific to viscutin molecules in the presence of other isobaric ions at m/z 137 occurring in compounds in other molecular families.

CONCLUSION

Therefore, the results of the current study showed that computational tools such as MS2LDA are essential in uncovering some gas-phase fragmentation reactions of molecules in MS and that theoretical modelling is a powerful tool in rationalising these reactions in metabolite identification.

DeepSAT: Learning Molecular Structures from Nuclear Magnetic Resonance Data

The identification of molecular structure is essential for understanding chemical diversity and for developing drug leads from small molecules. Nevertheless, the structure elucidation of small molecules by Nuclear Magnetic Resonance (NMR) experiments is often a long and non-trivial process that relies on years of training. To achieve this process efficiently, several spectral databases have been established to retrieve reference NMR spectra. However, the number of reference NMR spectra available is limited and has mostly facilitated annotation of commercially available derivatives. Here, we introduce DeepSAT, a neural network-based structure annotation and scaffold prediction system that directly extracts the chemical features associated with molecular structures from their NMR spectra. Using only the 1H-13C HSQC spectrum, DeepSAT identifies related known compounds and thus efficiently assists in the identification of molecular structures. DeepSAT is expected to accelerate chemical and biomedical research by accelerating the identification of molecular structures.

Application of feature-based molecular networking and MassQL for the MS/MS fragmentation study of depsipeptides

The Feature-based Molecular Networking (FBMN) is a well-known approach for mapping and identifying structures and analogues. However, in the absence of prior knowledge about the molecular class, assessing specific fragments and clusters requires time-consuming manual validation. This study demonstrates that combining FBMN and Mass Spec Query Language (MassQL) is an effective strategy for accelerating the decoding mass fragmentation pathways and identifying molecules with comparable fragmentation patterns, such as beauvericin and its analogues. To accomplish this objective, a spectral similarity network was built from ESI-MS/MS experiments of Fusarium oxysporum at various collision energies (CIDs) and paired with a MassQL search query for conserved beauvericin ions. FBMN analysis revealed that sodiated and protonated ions clustered differently, with sodiated adducts needing more collision energy and exhibiting a distinct fragmentation pattern. Based on this distinction, two sets of particular fragments were discovered for the identification of these hexadepsipeptides: ([M + H]+) m/z 134, 244, 262, and 362 and ([M + Na]+) m/z 266, 284 and 384. By using these fragments, MassQL accurately found other analogues of the same molecular class and annotated beauvericins that were not classified by FBMN alone. Furthermore, FBMN analysis of sodiated beauvericins at 70 eV revealed subclasses with distinct amino acid residues, allowing distinction between beauvericins (beauvericin and beauvericin D) and two previously unknown structural isomers with an unusual methionine sulfoxide residue. In summary, our integrated method revealed correlations between adduct types and fragmentation patterns, facilitated the detection of beauvericin clusters, including known and novel analogues, and allowed for the differentiation between structural isomers.

Bioactivity-guided isolation of trypanocidal coumarins and dihydro-pyranochromones from selected Apiaceae plant species

Bioactivity-guided isolation of natural products from plant matrices is widely used in drug discovery. Here, this strategy was applied to identify trypanocidal coumarins effective against the parasite Trypanosoma cruzi, the etiologic agent of Chagas disease (American trypanosomiasis). Previously, phylogenetic relationships of trypanocidal activity revealed a coumarin-associated antichagasic hotspot in the Apiaceae. In continuation, a total of 35 ethyl acetate extracts of different Apiaceae species were profiled for selective cytotoxicity against T. cruzi epimastigotes over host CHO-K1 and RAW264.7 cells at 10 μg/mL. A flow cytometry-based T. cruzi trypomastigote cellular infection assay was employed to measure toxicity against the intracellular amastigote stage. Among the tested extracts, Seseli andronakii aerial parts, Portenschlagiella ramosissima and Angelica archangelica subsp. litoralis roots exhibited selective trypanocidal activity and were subjected to bioactivity-guided fractionation and isolation by countercurrent chromatography. The khellactone ester isosamidin isolated from the aerial parts of S. andronakii emerged as a selective trypanocidal molecule (selectivity index ∼9) and inhibited amastigote replication in CHO-K1 cells, though it was significantly less potent than benznidazole. The khellactone ester praeruptorin B and the linear dihydropyranochromones 3'-O-acetylhamaudol and ledebouriellol isolated from the roots of P. ramosissima were more potent and efficiently inhibited the intracellular amastigote replication at < 10 μM. The furanocoumarins imperatorin, isoimperatorin and phellopterin from A. archangelica inhibited T. cruzi replication in host cells only in combination, indicative of superadditive effects, while alloimperatorin was more active in fractions. Our study reports preliminary structure-activity relationships of trypanocidal coumarins and shows that pyranocoumarins and dihydropyranochromones are potential chemical scaffolds for antichagasic drug discovery.

Targeted Isolation of Dolabellane Diterpenoids from the Soft Coral Clavularia viridis Using Molecular Networking

LC-MS/MS-based molecular networking annotation coupled ¹H NMR detection allowed the depiction of the soft coral Clavularia viridis to produce a profile of dolabellane-type diterpenoids. Chromatographic separation of the EtOAc fraction resulted in the isolation of 12 undescribed dolabellane-type diterpenoids, namely, clavirolides J-U (1-12). Their structures were characterized by the extensive analysis of the spectroscopic data, including the calculated ECD and X-ray diffraction for the configurational assignments. Clavirolides J-K are characterized by a 1,11- and 5,9-fused tricyclic tetradecane scaffold fused with a α,β-unsaturated-δ-lactone, and clavirolide L possesses a 1,11- and 3,5-fused tricyclic tetradecane scaffold, which extend the dolabellane-type scaffolds. Clavirolides L and G showed significant inhibition against HIV-1 without RT enzyme inhibition, providing additional non-nucleosides with different mechanisms from efavirenz.

Discovery of anti-SARS-CoV-2 secondary metabolites from the heartwood of Pterocarpus santalinus using multi-informative molecular networking

A pigment-depleted extract from the heartwood of Pterocarpus santalinus L. f. (PS-DE) showed promising anti-SARS-CoV-2 activity with an IC₅₀ of 29.9 μg/mL in Caco-2-F03 cells. To determine the potential active constituents within the extract prior to isolation, multi-informative molecular network (MN) was applied. Therefore, the extract was separated by high-performance counter-current chromatography (HPCCC) into 11 fractions which were subsequently tested for anti-SARS-CoV-2 activity and analysed by UPLC-tandem mass spectrometry (MS²). The resulting MN combines the bioactivity data of the fractions with the MS² data. The MN analysis led to the targeted isolation of seven compounds including one pterocarpan (7) reported for the first time as constituent of P. santalinus and four so far undescribed natural products (NPs) that belong to the compound classes of arylpropanes (9), isoflavanones (10) coumestans (16) and 3-arylcoumarins (17), respectively. In total, 15 constituents from the heartwood of P. santalinus and one synthetic isoflavonoid that is structurally related to the natural metabolites were tested for anti-SARS-CoV-2 activity. Thereby, the two pterocarpans (-)-homopterocarpin (5) and (-)-medicarpin (2), the stilbene (E)-pterostilbene (1) and the isoflavonoid 7-O-methylgenistein (11) showed a distinct antiviral activity with IC₅₀ values of 17.2, 33.4, 34.7, and 37.9 µM, respectively, and no cytotoxic effects against Caco-2-F03 cells (CC₅₀ > 100 µM). In addition, a structure-activity relationship (SAR) was proposed indicating structural requirements of pterocarpans for anti-SARS-CoV-2 activity. The herein presented results support the implementation of multi-informative molecular networks as powerful tool for dereplication and targeted isolation of bioactive NPs.

Structural identification of pyridinopyrone compounds with anti-neuroinflammatory activity from streptomyces sulphureus DSM 40104

This study investigated the chemical composition and biosynthesis pathway of compounds produced by Streptomyces sulphureus DSM 40104. With the guild of molecular networking analysis, we isolated and identified six uncommon structural characteristics of compounds, including four newly discovered pyridinopyrones. Based on genomic analysis, we proposed a possible hybrid NRPS-PKS biosynthesis pathway for pyridinopyrones. Notably, this pathway starts with the use of nicotinic acid as the starting unit, which is a unique feature. Compounds 1-3 exhibited moderate anti-neuroinflammatory activity against LPS-induced BV-2 cell inflammation. Our study demonstrates the diversity of polyene pyrone compounds regarding their chemical structure and bioactivity while providing new insights into their biosynthesis pathway. These findings may lead to the development of new treatments for inflammation-related diseases.

Tandem LC-MS Identification of Antitubercular Compounds in Zones of Growth Inhibition Produced by South African Filamentous Actinobacteria

Novel antitubercular compounds are urgently needed to combat drug-resistant Mycobacterium tuberculosis (Mtb). Filamentous actinobacteria have historically been an excellent source of antitubercular drugs. Despite this, drug discovery from these microorganisms has fallen out of favour due to the continual rediscovery of known compounds. To increase the chance of discovering novel antibiotics, biodiverse and rare strains should be prioritised. Subsequently, active samples need to be dereplicated as early as possible to focus efforts on truly novel compounds. In this study, 42 South African filamentous actinobacteria were screened for antimycobacterial activity using the agar overlay method against the Mtb indicator Mycolicibacterium aurum under six different nutrient growth conditions. Known compounds were subsequently identified through extraction and high-resolution mass spectrometric analysis of the zones of growth inhibition produced by active strains. This allowed the dereplication of 15 hits from six strains that were found to be producing puromycin, actinomycin D and valinomycin. The remaining active strains were grown in liquid cultures, extracted and submitted for screening against Mtb in vitro. Actinomadura napierensis B60^T was the most active sample and was selected for bioassay-guided purification. This resulted in the identification of tetromadurin, a known compound, but which we show for the first time to have potent antitubercular activity, with the MIC₉₀s within the range of 73.7-151.6 nM against M. tuberculosis H37Rv^Tin vitro under different test conditions. This shows that South African actinobacteria are a good source of novel antitubercular compounds and warrant further screening. It is also revealed that active hits can be dereplicated by HPLC-MS/MS analysis of the zones of growth inhibition produced by the agar overlay technique.

Advanced Methods for Natural Products Discovery: Bioactivity Screening, Dereplication, Metabolomics Profiling, Genomic Sequencing, Databases and Informatic Tools, and Structure Elucidation

Natural Products (NP) are essential for the discovery of novel drugs and products for numerous biotechnological applications. The NP discovery process is expensive and time-consuming, having as major hurdles dereplication (early identification of known compounds) and structure elucidation, particularly the determination of the absolute configuration of metabolites with stereogenic centers. This review comprehensively focuses on recent technological and instrumental advances, highlighting the development of methods that alleviate these obstacles, paving the way for accelerating NP discovery towards biotechnological applications. Herein, we emphasize the most innovative high-throughput tools and methods for advancing bioactivity screening, NP chemical analysis, dereplication, metabolite profiling, metabolomics, genome sequencing and/or genomics approaches, databases, bioinformatics, chemoinformatics, and three-dimensional NP structure elucidation.

Biosynthetic Enzyme-guided Disease Correlation Connects Gut Microbial Metabolites Sulfonolipids to Inflammatory Bowel Disease Involving TLR4 Signaling

The trillions of microorganisms inhabiting the human gut are intricately linked to human health. At the species abundance level, correlational studies have connected specific bacterial taxa to various diseases. While the abundances of these bacteria in the gut serve as good indicators for disease progression, understanding the functional metabolites they produce is critical to decipher how these microbes influence human health. Here, we report a unique biosynthetic enzyme-guided disease correlation approach to uncover microbial functional metabolites as potential molecular mechanisms in human health. We directly connect the expression of gut microbial sulfonolipid (SoL) biosynthetic enzymes to inflammatory bowel disease (IBD) in patients, revealing a negative correlation. This correlation is then corroborated by targeted metabolomics, identifying that SoLs abundance is significantly decreased in IBD patient samples. We experimentally validate our analysis in a mouse model of IBD, showing that SoLs production is indeed decreased while inflammatory markers are increased in diseased mice. In support of this connection, we apply bioactive molecular networking to show that SoLs consistently contribute to the immunoregulatory activity of SoL-producing human microbes. We further reveal that sulfobacins A and B, two representative SoLs, primarily target Toll-like receptor 4 (TLR4) to mediate immunomodulatory activity through blocking TLR4's natural ligand lipopolysaccharide (LPS) binding to myeloid differentiation factor 2, leading to significant suppression of LPS-induced inflammation and macrophage M1 polarization. Together, these results suggest that SoLs mediate a protective effect against IBD through TLR4 signaling and showcase a widely applicable biosynthetic enzyme-guided disease correlation approach to directly link the biosynthesis of gut microbial functional metabolites to human health.

Kvalheim O, Cech NB. Interaction Metabolomics to Discover Synergists in Natural Product Mixtures

Mass spectrometry metabolomics has become increasingly popular as an integral aspect of studies to identify active compounds from natural product mixtures. Classical metabolomics data analysis approaches do not consider the possibility that interactions (such as synergy) could occur between mixture components. With this study, we developed "interaction metabolomics" to overcome this limitation. The innovation of interaction metabolomics is the inclusion of compound interaction terms (CITs), which are calculated as the product of the intensities of each pair of features (detected ions) in the data matrix. Herein, we tested the utility of interaction metabolomics by spiking known concentrations of an antimicrobial compound (berberine) and a synergist (piperine) into a set of inactive matrices. We measured the antimicrobial activity for each of the resulting mixtures against Staphylococcus aureus and analyzed the mixtures with liquid chromatography coupled to high-resolution mass spectrometry. When the data set was processed without CITs (classical metabolomics), statistical analysis yielded a pattern of false positives. However, interaction metabolomics correctly identified berberine and piperine as the compounds responsible for the synergistic activity. To further validate the interaction metabolomics approach, we prepared mixtures from extracts of goldenseal (Hydrastis canadensis) and habañero pepper (Capsicum chinense) and correctly correlated synergistic activity of these mixtures to the combined action of berberine and several capsaicinoids. Our results demonstrate the utility of a conceptually new approach for identifying synergists in mixtures that may be useful for applications in natural products research and other research areas that require comprehensive mixture analysis.

Feature-Based Molecular Networking Facilitates the Comprehensive Identification of Differential Metabolites in Diabetic Cognitive Dysfunction Rats

Cognitive dysfunction is a frequent complication of type 2 diabetes mellitus (T2DM), usually accompanied by metabolic disorders. However, the metabolic changes in diabetic cognitive dysfunction (DCD) patients, especially compared to T2DM groups, are not fully understood. Due to the subtle differences in metabolic alterations between DCD groups and T2DM groups, the comprehensive detection of the untargeted metabolic profiles of hippocampus and urine samples of rats was conducted by LC-MS, considering the different ionization modes and polarities of the examined compounds, and feature-based molecular networking (FBMN) was performed to help identify differential metabolites from a comprehensive perspective in this study. In addition, an association analysis of the differential metabolites in hippocampus and urine was conducted by the O2PLS model. Finally, a total of 71 hippocampal tissue differential metabolites and 179 urine differential metabolites were identified. The pathway enrichment results showed that glutamine and glutamate metabolism, alanine, aspartate, and glutamate metabolism, glycerol phospholipid metabolism, TCA cycle, and arginine biosynthesis in the hippocampus of DCD animals were changed. Seven metabolites (AUC > 0.9) in urine appeared as key differential metabolites that might reflect metabolic changes in the target tissue of DCD rats. This study showed that FBMN facilitated the comprehensive identification of differential metabolites in DCD rats. The differential metabolites may suggest an underlying DCD and be considered as potential biomarkers for DCD. Large samples and clinical experiments are needed for the subsequent elucidation of the possible mechanisms leading to these alterations and the verification of potential biomarkers.

Constructing a Myxobacterial Natural Product Database to Facilitate NMR-Based Metabolomics Bioprospecting of Myxobacteria

Myxobacteria are fascinating prokaryotes featuring a potent capacity for producing a wealth of bioactive molecules with intricate chemical topology as well as intriguing enzymology, and thus it is critical to developing an efficient pipeline for bioprospecting. Herein, we construct the database MyxoDB, the first public compendium solely dedicated to myxobacteria, which enabled us to provide an overview of the structural diversity and taxonomic distribution of known myxobacterial natural products. Moreover, we demonstrated that the cutting-edge NMR-based metabolomics was effective to differentiate the biosynthetic priority of myxobacteria, whereby MyxoDB could greatly streamline the dereplication of multifarious known compounds and accordingly speed up the discovery of new compounds. This led to the rapid identification of a class of linear di-lipopeptides (archangimins) and a rare rearranged sterol (corasterol) that were endowed with unique chemical architectures and/or biosynthetic enzymology. We also showcased that NMR-based metabolomics, MyxoDB, and genomics can also work concertedly to accelerate the targeted discovery of a polyketidic compound pyxipyrrolone C. All in all, this study sets the stage for the discovery of many more novel natural products from underexplored myxobacterial resources.

Bioactivity-based molecular networking-guided identification of guttiferone J from Garcinia cambogia as an anti-obesity candidate

BACKGROUND AND PURPOSE

Pharmacological intervention to induce browning of white adipose tissue provides a promising anti-obesity therapy. The fruits of Garcinia cambogia (Clusiaceae) have been widely applied to manage body weight; however, the chemical principles remain unclear. The current study aims to discover browning inducers from the fruits of G. cambogia and investigate the underlying mechanisms.

EXPERIMENTAL APPROACH

The bioactivity-based molecular networking and Oil Red O staining on 3T3-L1 and C3H10T1/2 adipocytes were applied for guided isolation. High-fat diet-induced obese mice were recruited to evaluate the anti-obesity activity.

KEY RESULTS

The bioactivity-based molecular networking-guided isolation yielded several polycyclic polyprenylated acylphloroglucinols from the fruits of G. cambogia with lipid-lowering effect in adipocytes, including guttiferone J (GOJ), garcinol and 14-deoxygarcinol. As the most potent one, GOJ (10 μM) reduced lipid accumulation by 70% and 76% in 3T3-L1 and C3H10T1/2 adipocytes, respectively. Furthermore, GOJ (2.5-10 μM) increased the expression of the deacetylase sirtuin 3 (SIRT3) and activated it, which, in turn, reduced the acetylation level of PPARγ coactivator-1α to boost mitochondrial biogenesis and promoted uncoupling protein 1 expression to enhance thermogenesis, resulting in browning of adipocytes. In high-fat diet-induced-obese mice, GOJ (10 and 20 mg·kg^-1 ·day^-1 for 12 weeks) protected against adiposity, hyperlipidaemia, insulin resistance and liver lipotoxicity, through boosting SIRT3-mediated browning of inguinal adipose tissue.

CONCLUSION AND IMPLICATIONS

GOJ represents a new scaffold of thermogenic inducer, which is responsible for the anti-obesity property of G. cambogia and can be further developed as a candidate for treating obesity and its related disorders.

Integration of LC/MS, NMR and Molecular Docking for Profiling of Bioactive Diterpenes from Euphorbia mauritanica L. with in Vitro Anti-SARS-CoV-2 Activity

In spite of tremendous efforts exerted in the management of COVID-19, the absence of specific treatments and the prevalence of delayed and long-term complications termed post-COVID syndrome still urged all concerned researchers to develop a potent inhibitor of SARS-Cov-2. The hydromethanolic extracts of different parts of E. mauritanica were in vitro screened for anti-SARS-Cov-2 activity. Then, using an integrated strategy of LC/MS/MS, molecular networking and NMR, the chemical profile of the active extract was determined. To determine the optimum target for these compounds, docking experiments of the active extract's identified compounds were conducted at several viral targets. The leaves extract showed the best inhibitory effect with IC₅₀ 8.231±0.04 μg/ml. The jatrophane diterpenes were provisionally annotated as the primary metabolites of the bioactive leaves extract based on multiplex of LC/MS/MS, molecular network, and NMR. In silico studies revealed the potentiality of the compounds in the most active extract to 3CLpro, where compound 20 showed the best binding affinity. Further attention should be paid to the isolation of various jatrophane diterpenes from Euphorbia and evaluating their effects on SARS-Cov-2 and its molecular targets.

Metabolomics- and systems-biology-guided discovery of metabolite lead compounds and druggable targets

Metabolomics enables the comprehensive and unbiased analysis of metabolites and lipids in biological systems. In conjunction with high-throughput activity screening, big data and synthetic biology, metabolomics can guide the discovery of lead compounds with pharmacological activity from natural sources and the gut microbiome. In combination with other omics, metabolomics can further unlock the elucidation of compound toxicity, the mode of action and novel druggable targets of disease. Here, we discuss the workflows, limitations and future opportunities to leverage metabolomics and big data in conjunction with systems and synthetic biology for streamlining the discovery and development of molecules of pharmaceutical interest.

Targeted isolation of sesquiterpene lactone dimers from Aucklandia lappa guided by LC-HRMS/MS-based molecular networking

An LC-HRMS/MS-based molecular networking strategy was applied to investigate the potential sesquiterpene dimers of Aucklandia lappa, leading to the isolation of three undescribed guaiane-guaiane dimers and one guaiane-eudesmane dimer together with six known sesquiterpenes. The structures were determined by analyzing their 1D, 2D NMR, and HRESIMS data as well as ECD calculations. The biogenetic pathway of the sesquiterpene dimers was postulated to involve the Diels-Alder cycloaddition as the key step. All compounds exhibited their inhibitory effects on LPS-induced nitric oxide production in RAW 264.7 macrophages with IC₅₀ values ranging from 0.3 to 25.1 μM.

Rapid screening of neuraminidase inhibitors using an at-line nanofractionation platform involving parallel oseltamivir-sensitive/resistant neuraminidase bioassays

In this study, an advanced at-line nanofractionation based screening platform was developed to screen potential neuraminidase inhibitors (NAIs) from Lonicera japonica Thunb by involving two parallel bioassays, for determining both oseltamivir-sensitive neuraminidase (NAS) and oseltamivir-resistant neuraminidase (NAR) inhibitory activities. 20 potential NAIs with both NAS and NAR inhibitory effects were screened from Lonicera japonica Thunb and identified by mass spectrometer, including 11 phenolic acids, 8 flavonoids and one iridoid glycoside. The proposed at-line nanofractionation based screening platform for NAIs was also used to rapidly screen nine batches of water extracts of Lonicera japonica Thunb or its similar species. Clear differences in the number and content of active components were easily observed, demonstrating that the proposed method possesses great potential for the quality control of herb medicines.

Microbial Metabolites Annotation by Mass Spectrometry-Based Metabolomics

Since the discovery of penicillin, microbial metabolites have been extensively investigated for drug discovery purposes. In the last decades, microbial derived compounds have gained increasing attention in different fields from pharmacognosy to industry and agriculture. Microbial metabolites in microbiomes present specific functions and can be associated with the maintenance of the natural ecosystems. These metabolites may exhibit a broad range of biological activities of great interest to human purposes. Samples from either microbial isolated cultures or microbiomes consist of complex mixtures of metabolites and their analysis are not a simple process. Mass spectrometry-based metabolomics encompass a set of analytical methods that have brought several improvements to the microbial natural products field. This analytical tool allows the comprehensively detection of metabolites, and therefore, the access of the chemical profile from those biological samples. These analyses generate thousands of mass spectra which is challenging to analyse. In this context, bioinformatic metabolomics tools have been successfully employed to accelerate and facilitate the investigation of specialized microbial metabolites. Herein, we describe metabolomics tools used to provide chemical information for the metabolites, and furthermore, we discuss how they can improve investigation of microbial cultures and interactions.

Mass Spectroscopy as an Analytical Tool to Harness the Production of Secondary Plant Metabolites: The Way Forward for Drug Discovery

The molecular map of diverse biological molecules linked with structure, function, signaling, and regulation within a cell can be elucidated using an analytically demanding omic approach. The latest trend of using "metabolomics" technologies has explained the natural phenomenon of opening a new avenue to understand and enhance bioactive compounds' production. Examination of sequenced plant genomes has revealed that a considerable portion of these encodes genes of secondary metabolism. In addition to genetic and molecular tools developed in the current era, the ever-increasing knowledge about plant metabolism's biochemistry has initiated an approach for wisely designed, more productive genetic engineering of plant secondary metabolism for improved defense systems and enhanced biosynthesis of beneficial metabolites. Secondary plant metabolites are natural products synthesized by plants that are not directly involved with their average growth and development but play a vital role in plant defense mechanisms. Plant secondary metabolites are classified into four major classes: terpenoids, phenolic compounds, alkaloids, and sulfur-containing compounds. More than 200,000 secondary metabolites are synthesized by plants having a unique and complex structure. Secondary plant metabolites are well characterized and quantified by omics approaches and therefore used by humans in different sectors such as agriculture, pharmaceuticals, chemical industries, and biofuel. The aim is to establish metabolomics as a comprehensive and dynamic model of diverse biological molecules for biomarkers and drug discovery. In this chapter, we aim to illustrate the role of metabolomic technology, precisely liquid chromatography-mass spectrometry, capillary electrophoresis mass spectrometry, gas chromatography-mass spectrometry, and nuclear magnetic resonance spectroscopy, specifically as a research tool in the production and identification of novel bioactive compounds for drug discovery and to obtain a unified insight of secondary metabolism in plants.