Revisiting Previously Investigated Plants: A Molecular Networking-Based Study of Geissospermum laeve

Combination of Machine Learning and Empirical Computation for the Structural Validation of Trirosaline, a Natural Trimeric Monoterpene Indole Alkaloid from Catharanthus roseus

Chemical investigation of the emblematic Catharanthus roseus led to the discovery of trirosaline (1), the first example of a tris-ajmalicine-type monoterpene indole alkaloid and the first natural trimeric MIA ever reported from this deeply dug plant species. Its structure was primarily elucidated based on NMR and HRESIMS analyses, and the nature of its unique intermonomeric linkages was firmly confirmed based on a combination of empirical computation and ML-J-DP4 study. Its absolute configuration was mitigated by comparison of experimental and TDDFT-simulated electronic circular dichroism (ECD) spectra. A possible biosynthetic pathway for trirosaline (1) was postulated.

Putative Identification of New Phragmaline-Type Limonoids from the Leaves of Swietenia macrophylla King: A Case Study Using Mass Spectrometry-Based Molecular Networking

Swietenia macrophylla King is a plant commonly known as Brazilian mahogany. The wood from its stem is highly prized for its exceptional quality, while its leaves are valued for their high content of phragmalin-type limonoids, a subclass of compounds known for their significant biological activities, including antimalarial, antitumor, antiviral, and anti-inflammatory properties. In this context, twelve isolated limonoids from S. macrophylla leaves were employed as standards in mass spectrometry-based molecular networking to unveil new potential mass spectrometry signatures for phragmalin-type limonoids. Consequently, ultra-performance liquid chromatography coupled with high-resolution mass spectrometry was utilized for data acquisition. Subsequently, the obtained data were analyzed using the Global Natural Products Social Molecular Networking platform based on spectral similarity. In summary, this study identified 24 new putative phragmalin-type limonoids for the first time in S. macrophylla. These compounds may prove valuable in guiding future drug development efforts, leveraging the already established biological activities associated with limonoids.

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.

Indole Alkaloids of Rauvolfia ligustrina and Their Anxiolytic Effects in Adult Zebrafish

Rauvolfia species are well known as producers of bioactive monoterpene indole alkaloids, which exhibit a broad spectrum of biological activities. A new vobasine-sarpagan-type bisindole alkaloid (1: ) along with six known monomeric indoles (2, 3/4, 5: , and 6/7: ) were isolated from the ethanol extract of the roots of Rauvolfia ligustrina. The structure of the new compound was elucidated by interpretation of their spectroscopic data (1D and 2D NMR and HRESIMS) and comparison with published data for analog compounds. The cytotoxicity of the isolated compounds was screened in a zebrafish (Danio rerio) model. The possible GABAergic (diazepam as the positive control) and serotoninergic (fluoxetine as the positive control) mechanisms of action in adult zebrafish were also evaluated. No compounds were cytotoxic. Compound 2: and the epimers 3: /4: and 6: /7: showed a mechanism action by GABAA, while compound 1: showed a mechanism action by a serotonin receptor (anxiolytic activity). Molecular docking studies showed that compounds 2: and 5: have a greater affinity by the GABAA receptor when compared with diazepam, whereas 1: showed the best affinity for the 5HT2AR channel when compared to risperidone.

An insight into the recent developments in anti-infective potential of indole and associated hybrids

Prevention, accurate diagnosis, and effective treatment of infections are the main challenges in the overall management of infectious diseases. The best example is the ongoing SARs-COV-2(COVID-19) pandemic; the entire world is extremely worried about at present. Interestingly, heterocyclic moieties provide an ideal scaffold on which suitable pharmacophores can be designed to construct novel drugs. Indoles are amongst the most essential class of heteroaromatics in medicinal chemistry, which are ubiquitous across natural sources. The aforesaid derivatives have become invaluable scaffolds because of their wide spectrum therapeutic applications. Therefore, many researchers are focused on the design and synthesis of indole and associated hybrids of biological relevance. Hence, in the present review, we concisely discuss the indole containing natural sources, marketed drugs, clinical candidates, and their biological activities like antibacterial, antifungal, anti-TB, antiviral, antimalarial, and anti-leishmanial activities. The structure-activity relationships study of indole derivatives is also presented for a better understanding of the identified structures. The literature data presented for the anti-infective agents herein covers largely for the last twelve years.

Exploration by molecular networking of Strychnos alkaloids reveals the unexpected occurrence of strychnine in seven Strychnos species

INTRODUCTION

Plants of the Strychnos genus, which include about 200 species, are used for multiple traditional purposes as hunting poison, for example, and have shown interesting pharmacological properties, especially curarizing and tetanizing, but also against malaria. Many monoterpene indole alkaloids have already been isolated and identified. Among them, there is strychnine, a famous alkaloid that can cause death by asphyxiation.

OBJECTIVE

Investigate alkaloidic molecular diversity from Strychnos genus using molecular networking technique and study the Strychnos genus from a chemotaxonomic point of view.

MATERIAL AND METHODS

Twenty-eight different species and different plant parts were ground into powder using a grinder. The methanolic extracts were carried out using a pressurized solvent extraction and the alkaloid extract was performed manually with a separating funnel. The extracts were analyzed by HPLC-ESI(+)-Q/TOF. The data were processed using MZmine 2 software and the molecular network was generated on the GNPS platform. The study of the generated molecular network allowed the detection of various alkaloids. Among these is the famous strychnine which has been detected in 7 new Strychnos species not yet described as strychnine producers. This identification was investigated using orthogonal approaches, namely TLC, NMR, HPLC-UV and UHPLC-ESI(+)-Q/TOF analyses. The LOD by HPLC-UV of strychnine was also determined.

RESULTS

Further analyses allowed to confirm the presence of strychnine in S. densiflora trunk barks but also to show the presence of strychnine with high probability in the trunk barks of S. camptoneura, S. congolana, S. boonei, and S. tchibangensis, and in the leaves of S. usambarensis. About the trunk barks of S. tricalyisoides, the probability of a strychnine content remains low.

CONCLUSION

This work exemplified the efficiency of molecular networking in identifying known metabolites (major and minor alkaloids) involved in the chemotaxonomic study of plants from Strychnos genus.

Combination of GC-MS Molecular Networking and Larvicidal Effect against Aedes aegypti for the Discovery of Bioactive Substances in Commercial Essential Oils

Dengue is a neglected disease, present mainly in tropical countries, with more than 5.2 million cases reported in 2019. Vector control remains the most effective protective measure against dengue and other arboviruses. Synthetic insecticides based on organophosphates, pyrethroids, carbamates, neonicotinoids and oxadiazines are unattractive due to their high degree of toxicity to humans, animals and the environment. Conversely, natural-product-based larvicides/insecticides, such as essential oils, present high efficiency, low environmental toxicity and can be easily scaled up for industrial processes. However, essential oils are highly complex and require modern analytical and computational approaches to streamline the identification of bioactive substances. This study combined the GC-MS spectral similarity network approach with larvicidal assays as a new strategy for the discovery of potential bioactive substances in complex biological samples, enabling the systematic and simultaneous annotation of substances in 20 essential oils through LC50 larvicidal assays. This strategy allowed rapid intuitive discovery of distribution patterns between families and metabolic classes in clusters, and the prediction of larvicidal properties of acyclic monoterpene derivatives, including citral, neral, citronellal and citronellol, and their acetate forms (LC50 < 50 µg/mL).

Ethnobotany and the Role of Plant Natural Products in Antibiotic Drug Discovery

The crisis of antibiotic resistance necessitates creative and innovative approaches, from chemical identification and analysis to the assessment of bioactivity. Plant natural products (NPs) represent a promising source of antibacterial lead compounds that could help fill the drug discovery pipeline in response to the growing antibiotic resistance crisis. The major strength of plant NPs lies in their rich and unique chemodiversity, their worldwide distribution and ease of access, their various antibacterial modes of action, and the proven clinical effectiveness of plant extracts from which they are isolated. While many studies have tried to summarize NPs with antibacterial activities, a comprehensive review with rigorous selection criteria has never been performed. In this work, the literature from 2012 to 2019 was systematically reviewed to highlight plant-derived compounds with antibacterial activity by focusing on their growth inhibitory activity. A total of 459 compounds are included in this Review, of which 50.8% are phenolic derivatives, 26.6% are terpenoids, 5.7% are alkaloids, and 17% are classified as other metabolites. A selection of 183 compounds is further discussed regarding their antibacterial activity, biosynthesis, structure-activity relationship, mechanism of action, and potential as antibiotics. Emerging trends in the field of antibacterial drug discovery from plants are also discussed. This Review brings to the forefront key findings on the antibacterial potential of plant NPs for consideration in future antibiotic discovery and development efforts.

Streamlined targeting of Amaryllidaceae alkaloids from the bulbs of Crinum scillifolium using spectrometric and taxonomically-informed scoring metabolite annotations

Four undescribed alkaloids have been isolated from the bulbs of the previously unstudied Crinum scillifolium. These compounds were targeted following a state-of-the-art molecular networking strategy comprising a dereplication against in silico databases and re-ranking of the candidate structures based on taxonomically informed scoring. The unreported structures span across a variety of Amaryllidaceae alkaloids appendages. Their structures were unambiguously elucidated by thorough interpretation of their HRESIMS and 1D and 2D NMR data, and comparison to literature data. DFT-NMR calculations were performed to support the determined relative configurations of scillitazettine and scilli-N-desmethylpretazettine and their absolute configurations were mitigated by comparison between experimental and theoretically calculated ECD spectra. The lack of a methyl group on the nitrogen atom in the structure of scilli-N-desmethylpretazettine series is highly unusual in the pretazettine/tazettine series but the most original structural feature in it lies in its 11α disposed hydrogen, which is new to pretazettines. The antiplasmodial as well as the cytotoxic activities against the human colon cancer cell line HCT116 were evaluated, revealing mild to null activities.

Hetiamacin E and F, New Amicoumacin Antibiotics from Bacillus subtilis PJS Using MS/MS-Based Molecular Networking

To combat escalating levels of antibiotic resistance, novel strategies are developed to address the everlasting demand for new antibiotics. This study aimed at investigating amicoumacin antibiotics from the desert-derived Bacillus subtilis PJS by using the modern MS/MS-based molecular networking approach. Two new amicoumacins, namely hetiamacin E (1) and hetiamacin F (2), were finally isolated. The planar structures were determined by analysis of extensive NMR spectroscopic and HR-ESI-MS data, and the absolute configurations were concluded by analysis of the CD spectrum. Hetiamacin E (1) showed strong antibacterial activities against methicillin-sensitive and resistant Staphylococcus epidermidis at 2-4 µg/mL, and methicillin-sensitive and resistant Staphylococcus aureus at 8-16 µg/mL. Hetiamacin F (2) exhibited moderate antibacterial activities against Staphylococcus sp. at 32 µg/mL. Both compounds were inhibitors of protein biosynthesis demonstrated by a double fluorescent protein reporter system.

Geissoschizoline, a promising alkaloid for Alzheimer's disease: Inhibition of human cholinesterases, anti-inflammatory effects and molecular docking

Due to the lack of effective pharmacotherapy options to treats Alzheimer's disease, new strategies have been approached in the search for multi-target molecules as therapeutic options. In this work, four indole alkaloids, geissoschizoline, geissoschizone, geissospermine, and 3',4',5',6'-tetradehydrogeissospermine were isolated from Geissospermum vellosii (Pao pereira) and evaluated for their anticholinesterase activities. While geissospermine inhibited only butyrylcholinesterase (BChE), the other alkaloids behaved as non-selective inhibitors of acetylcholinesterase (AChE) and BChE. In cell viability tests, only geissoschizoline was not cytotoxic. Therefore, geissoschizoline actions were also evaluated in human cholinesterases, where it was twice as potent inhibitor of hBChE (IC₅₀ = 10.21 ± 0.01 µM) than hAChE (IC₅₀ = 20.40 ± 0.93 µM). On enzyme kinetic studies, geissoschizoline presented a mixed-type inhibition mechanism for both enzymes. Molecular docking studies pointed interactions of geissoschizoline with active site and peripheral anionic site of hAChE and hBChE, indicating a dual site inhibitor profile. Moreover, geissoschizoline also played a promising anti-inflammatory role, reducing microglial release of NO and TNF-α at a concentration (1 μM) ten and twenty times lower than the IC₅₀ values of hBChE and hAChE inhibition, respectively. These actions give geissoschizoline a strong neuroprotective character. In addition, the ability to inhibit hAChE and hBChE, with approximate inhibitory potencies, accredits this alkaloid for therapeutic use in the moderate to severe phase of AD. Thus, geissoschizoline emerges as a possible multi-target prototype that can be very useful in preventing neurodegeneration and restore neurotransmission.

Structural characterization and discrimination of Paris polyphylla var. yunnanensis by a molecular networking strategy coupled with ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry

RATIONALE

Paris polyphylla var. yunnanensis (Franch) Hand Mazz (PPY) is a traditional Chinese medicine with antitumor, antibacterial, hemostatic, and anthelmintic activities. Identification of the chemical composition in PPY is helpful to discover its active ingredients and can be used to establish its quality control protocols.

METHODS

The composition of PPY was identified using ultra-high-performance liquid chromatography combined with quadrupole time-of-flight mass spectrometry (UHPLC/QTOF-MS/MS) coupled with a molecular networking strategy. First, the UHPLC/QTOF-MS/MS approach was optimized for chemical compound profiling. Then, the MS data were processed using PeakView™ combined with an in-house database to quickly characterize the secondary metabolites. Finally, molecular networking excavated new molecular weights to discover unknown or trace natural products based on the characteristics of each cluster.

RESULTS

A total of 222 compounds, including 77 isospirostanols, 2 spirostanols, 19 furostanols, 10 pseudospirostanols, 6 cholesterols, 10 C₂₁ steroids, 5 insect metamorphosis hormones, 3 plant sterols, 6 five-ring triterpenoids, 4 flavonoids, 8 fatty acids, 2 phenylpropanoids, and 8 other compounds, were characterized in PPY by comparing their main fragmentation characteristics and pathways with the literature data, and 62 of them, 54 steroidals and 8 phenylpropanoids, were discovered or tentatively identified for the first time.

CONCLUSIONS

This study extended the application of a molecular networking strategy to traditional herbal medicines and developed a molecular networking based screening approach with a significant increase in efficiency for the discovery and identification of trace novel natural products.

Molecular Networking Reveals Serpentinine-Related Bisindole Alkaloids from Picralima nitida, a Previously Well-Investigated Species

Five new monoterpene indole alkaloids (1-5), including four serpentinine-related bisindoles and one alstonine derivative monomer, have been isolated from the aerial parts of Picralima nitida. Their structures were elucidated by analysis of their HRMS and NMR spectroscopic data, and their absolute configurations were deduced from the comparison of experimental and simulated ECD spectra. In addition, two known compounds (6 and 7), previously undescribed from P. nitida, have also been purified. The compound isolation workflow was guided by a molecular networking-based dereplication strategy. Twenty-three compounds were dereplicated from the EtOH extract of P. nitida and fractions network and were assigned various levels of identification confidence. The antiparasitic activities against Plasmodium falciparum as well as the cytotoxic activity against the MRC-5 cell line were determined for compounds 1-7.

Current status and contemporary approaches to the discovery of antitumor agents from higher plants

Higher plant constituents have afforded clinically available anticancer drugs. These include both chemically unmodified small molecules and their synthetic derivatives currently used or those in clinical trials as antineoplastic agents, and an updated summary is provided. In addition, botanical dietary supplements, exemplified by mangosteen and noni constituents, are also covered as potential cancer chemotherapeutic agents. Approaches to metabolite purification, rapid dereplication, and biological evaluation including analytical hyphenated techniques, molecular networking, and advanced cellular and animal models are discussed. Further, enhanced and targeted drug delivery systems for phytochemicals, including micelles, nanoparticles and antibody drug conjugates (ADCs) are described herein.

Innovative omics-based approaches for prioritisation and targeted isolation of natural products - new strategies for drug discovery

Covering: 2013 to 2019 The exploration of the chemical diversity of extracts from various biological sources has led to major drug discoveries. Over the past two decades, despite the introduction of advanced methodologies for natural product (NP) research (e.g., dereplication and high content screening), successful accounts of the validation of NPs as lead therapeutic candidates have been limited. In this context, one of the main challenges faced is related to working with crude natural extracts because of their complex composition and the inadequacies of classical bioguided isolation studies given the pace of high-throughput screening campaigns. In line with the development of metabolomics, genomics and chemometrics, significant advances in metabolite profiling have been achieved and have generated high-quality massive genome and metabolome data on natural extracts. The unambiguous identification of each individual NP in an extract using generic methods remains challenging. However, the establishment of structural links among NPs via molecular network analysis and the determination of common features of extract composition have provided invaluable information to the scientific community. In this context, new multi-informational-based profiling approaches integrating taxonomic and/or bioactivity data can hold promise for the discovery and development of new bioactive compounds and return NPs back to an exciting era of development. In this article, we examine recent studies that have the potential to improve the efficiency of NP prioritisation and to accelerate the targeted isolation of key NPs. Perspectives on the field's evolution are discussed.

Antiplasmodial natural products: an update

Background

Malaria remains a significant public health challenge in regions of the world where it is endemic. An unprecedented decline in malaria incidences was recorded during the last decade due to the availability of effective control interventions, such as the deployment of artemisinin-based combination therapy and insecticide-treated nets. However, according to the World Health Organization, malaria is staging a comeback, in part due to the development of drug resistance. Therefore, there is an urgent need to discover new anti-malarial drugs. This article reviews the literature on natural products with antiplasmodial activity that was reported between 2010 and 2017.

Methods

Relevant literature was sourced by searching the major scientific databases, including Web of Science, ScienceDirect, Scopus, SciFinder, Pubmed, and Google Scholar, using appropriate keyword combinations.

Results and Discussion

A total of 1524 compounds from 397 relevant references, assayed against at least one strain of Plasmodium, were reported in the period under review. Out of these, 39% were described as new natural products, and 29% of the compounds had IC₅₀ ≤ 3.0 µM against at least one strain of Plasmodium. Several of these compounds have the potential to be developed into viable anti-malarial drugs. Also, some of these compounds could play a role in malaria eradication by targeting gametocytes. However, the research into natural products with potential for blocking the transmission of malaria is still in its infancy stage and needs to be vigorously pursued.

Computational methods for NMR and MS for structure elucidation II: database resources and advanced methods

Technological advances have contributed to the evolution of the natural product chemistry and drug discovery programs. Recently, computational methods for nuclear magnetic resonance (NMR) and mass spectrometry (MS) have speeded up and facilitated the process of structural elucidation even in high complex biological samples. In this chapter, the current computational tools related to NMR and MS databases and spectral similarity networks, as well as their applications on dereplication and determination of biological biomarkers, are addressed.

Exploring novel secondary metabolites from natural products using pre-processed mass spectral data

Many natural product chemists are working to identify a wide variety of novel secondary metabolites from natural materials and are eager to avoid repeatedly discovering known compounds. Here, we developed liquid chromatography/mass spectrometry (LC/MS) data-processing protocols for assessing high-throughput spectral data from natural sources and scoring the novelty of unknown metabolites from natural products. This approach automatically produces representative MS spectra (RMSs) corresponding to single secondary metabolites in natural sources. In this study, we used the RMSs of Agrimonia pilosa roots and aerial parts as models to reveal the structural similarities of their secondary metabolites and identify novel compounds, as well as isolation of three types of nine new compounds including three pilosanidin- and four pilosanol-type molecules and two 3-hydroxy-3-methylglutaryl (HMG)-conjugated chromones. Furthermore, we devised a new scoring system, the Fresh Compound Index (FCI), which grades the novelty of single secondary metabolites from a natural material using an in-house database constructed from 466 representative medicinal plants from East Asian countries. We expect that the FCIs of RMSs in a sample will help natural product chemists to discover other compounds of interest with similar chemical scaffolds or novel compounds and will provide insights relevant to the structural diversity and novelty of secondary metabolites in natural products.

CANPA: Computer-Assisted Natural Products Anticipation

Traditional natural products discovery workflows implying a combination of different targeting strategies, including structure- and/or bioactivity-based approaches, afford no information about new compound structures until late in the discovery pipeline. By integrating a MS/MS prediction module and a collaborative library of (bio)chemical transformations, we have developed a new platform, coined MetWork, that is capable of anticipating the structural identity of metabolites starting from any identified compound. In our quest to discover new monoterpene indole alkaloids, we demonstrate the utility of the MetWork platform by anticipating the structures of five previously undescribed sarpagine-like N-oxide alkaloids that have been targeted and isolated from the leaves of Alstonia balansae using a molecular networking-based dereplication strategy fueled by computer-generated annotations. This study constitutes the first example of nonpeptidic molecular networking-based natural product discovery workflow, in which the targeted structures were initially generated, and therefore anticipated by a computer prior to their isolation.

Natural products targeting strategies involving molecular networking: different manners, one goal

Covering: up to 2019Landmark advances in bioinformatics tools have recently enhanced the field of natural products research, putting today's natural product chemists in the enviable position of being able to perform the efficient targeting/discovery of previously undescribed molecules by expediting the prioritization of the isolation workflow. Among these advances, MS/MS molecular networking has appeared as a promising approach to dereplicate complex natural product mixtures, leading to a real revolution in the "art of natural product isolation" by accelerating the pace of research of this field. This review illustrates through selected cornerstone studies the new thinking in natural product isolation by drawing a parallel between the different underlying philosophies behind the use of molecular networking in targeting natural products.

Collected mass spectrometry data on monoterpene indole alkaloids from natural product chemistry research

This Data Descriptor announces the submission to public repositories of the monoterpene indole alkaloid database (MIADB), a cumulative collection of 172 tandem mass spectrometry (MS/MS) spectra from multiple research projects conducted in eight natural product chemistry laboratories since the 1960s. All data have been annotated and organized to promote reuse by the community. Being a unique collection of these complex natural products, these data can be used to guide the dereplication and targeting of new related monoterpene indole alkaloids within complex mixtures when applying computer-based approaches, such as molecular networking. Each spectrum has its own accession number from CCMSLIB00004679916 to CCMSLIB00004680087 on the GNPS. The MIADB is available for download from MetaboLights under the identifier: MTBLS142 (https://www.ebi.ac.uk/metabolights/MTBLS142).

Design Type(s)	mass spectrometry data transformation objective • mass spectrometry data analysis objective • data integration objective
Measurement Type(s)	mass spectrum
Technology Type(s)	liquid chromatography-tandem mass spectrometry
Factor Type(s)
Sample Characteristic(s)	Strychnos usambarensis • Picralima nitida • Geissospermum laeve • Pleiocarpa mutica • Alstonia • Callichilia inaequalis • Chimarris cymosa • Mostuea brunonis • Gonioma < moth > • Cinchona • Catharanthus roseus • Voacanga grandifolia

Machine-accessible metadata file describing the reported data (ISA-Tab format)

The value of universally available raw NMR data for transparency, reproducibility, and integrity in natural product research

Covering: up to 2018With contributions from the global natural product (NP) research community, and continuing the Raw Data Initiative, this review collects a comprehensive demonstration of the immense scientific value of disseminating raw nuclear magnetic resonance (NMR) data, independently of, and in parallel with, classical publishing outlets. A comprehensive compilation of historic to present-day cases as well as contemporary and future applications show that addressing the urgent need for a repository of publicly accessible raw NMR data has the potential to transform natural products (NPs) and associated fields of chemical and biomedical research. The call for advancing open sharing mechanisms for raw data is intended to enhance the transparency of experimental protocols, augment the reproducibility of reported outcomes, including biological studies, become a regular component of responsible research, and thereby enrich the integrity of NP research and related fields.

13C-NMR dereplication of Garcinia extracts: Predicted chemical shifts as reliable databases

Usually isolated from Garcinia (Clusiaceae) or Hypericum (Hypericaceae) species, some Polycyclic Polyprenylated AcylPhloroglucinols (PPAPs) have been recently reported as potential research tools for immunotherapy. Aiming at exploring the chemodiversity of PPAPs amongst Garcinia genus, a dereplication process suitable for such natural compounds has been developed. Although less sensitive than mass spectrometry, NMR spectroscopy is perfectly reproducible and allows stereoisomers distinction, justifying the development of ¹³C-NMR strategies. Dereplication requires the use of databases (DBs). To define if predicted DBs were accurate enough as dereplication tools, experimental and predicted δ_C of natural products usually isolated from Clusiaceae were compared. The ACD/Labs commercial software allowed to predict 73% of δ_C in a 1.25 ppm range around the experimental values. Consequently, with these parameters, the major PPAPs from a Garcinia bancana extract were successfully identified using a predicted DB.

Clerodane furanoditerpenoids as the probable cause of toxic hepatitis induced by Tinospora crispa

Tinospora crispa is a popular traditional herbal plant commonly used throughout the world for treatment of various diseases, in particular type 2 diabetes mellitus. We report here a new case of toxic hepatitis in a 57-year old male patient in the French West Indies following the consumption of two aqueous extracts of fresh Tinospora crispa stems. It thus differs from two previously reported cases that concerned the chronic intake of powdered dry stems delivered in solid oral dosage forms (i.e. pellets and tablets). Liquid Chromatography-Diode Array Detection-Mass Spectrometry (LC/DAD/MS) analyses were performed on an aqueous extract of the offending sample that mimics the swallowed preparation. They revealed the presence of species-specific molecular marker borapetoside C (1) and thus enabled an unambiguous phytochemical identification. The exploration of tandem MS/MS data obtained by ultra-high performance liquid chromatography/electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-HRMS) allowed the identification of 17 additional cis-clerodane-type furanoditerpenoid lactones, analogues of 1. These results support the hypothesis that the mechanisms underlying hepatotoxicity of Tinospora crispa are the same as those encountered with furanoditerpenoids-containing plants such as Teucrium chamaedrys or Dioscorea bulbifera. In the context of type 2 diabetes treatment, we recommend that Tinospora crispa intake should be more closely monitored for signs of hepatotoxicity.

Targeted Isolation of Neuroprotective Dicoumaroyl Neolignans and Lignans from Sageretia theezans Using in Silico Molecular Network Annotation Propagation-Based Dereplication

The integration of LC-MS/MS molecular networking and in silico MS/MS fragmentation is an emerging method for dereplication of natural products. In the present study, a targeted isolation of natural products using a new in silico-based annotation tool named Network Annotation Propagation (NAP) is described. NAP improves accuracy of in silico fragmentation analyses by reranking candidate structures based on the network topology from MS/MS-based molecular networking. Annotation for the MS/MS spectral network of the Sageratia theezans twig extract was performed using NAP, and most molecular families within the network, including the known triterpenoids 1-7, could be putatively annotated, without relying on any previous reports of molecules from this species. Based on the in silico dereplication results, molecules were prioritized for isolation. In total, six dicoumaroyl 8- O-4' neolignans (8-13) and three dicoumaroyl lignans (14-16) were isolated from the twigs of S. theezans and structurally characterized by spectroscopic analyses. Isolates were evaluated for their neuroprotective activity, and compounds 14-16 showed potent protective effects against glutamate-induced oxidative stress in mouse HT22 cells at a concentration of 12.5 μM.

Resolving the (19 R) Absolute Configuration of Lanciferine, a Monoterpene Indole Alkaloid from Alstonia boulindaensis

Reinvestigation of the structure of lanciferine (1a) through extensive spectroscopic analysis in conjunction with a detailed computational study led to the unambiguous assignment of its (19 R) absolute configuration, thus leading to the full (2 R, 3 S, 7 S, 15 R, 16 R, 19 R, 20 S) assignment of lanciferine 45 years after its isolation.

Targeted Isolation of Monoterpene Indole Alkaloids from Palicourea sessilis

Phytochemical investigation of the alkaloid extract of Palicourea sessilis by LC-HRMS/MS using molecular networking and an in silico MS/MS fragmentation approach suggested the presence of several new monoterpene indole alkaloids. These compounds were isolated by semipreparative HPLC, and their structures confirmed by means of HRMS, NMR, and ECD measurements as 4-N-methyllyaloside (3), 4-N-methyl-3,4-dehydrostrictosidine (4), 4β-hydroxyisodolichantoside (6), and 4α-hydroxyisodolichantoside (7), as well as the known alkaloids alline (1), N-methyltryptamine (2), isodolichantoside (5), and 5-oxodolichantoside (8). In addition, the acetylcholinesterase inhibitory activity of the compounds was evaluated up to 50 μM.