Isolation and Bioactivity of Natural Products from Streptomyces sp. MA37

The isolation and characterization of bioactive metabolites from Streptomyces species continue to represent a vital area of research, given their potential in natural product drug discovery. In this study, we characterize a new siderophore called legonoxamine I, together with a known compound, streptimidone, from the talented soil bacterium Streptomyces sp. MA37, using chromatographic techniques and spectroscopic analysis. Legonoxamine I is a new holo-siderophore, which is likely to be a derailed product from the biosynthetic pathway of legonoxamine A. We also demonstrate that legonoxamine A possesses potent anticancer activity (IC50 = 2.2 µM), exhibiting a remarkable ~30-fold increase in potency against MCF-7 ATCC HTB-22 breast cancer cells compared to desferrioxamine B, a structural analogue of legonoxamine A (IC50 = 61.1 µM). Comparing the structural difference between legonoxamine A and desferrioxamine B, it is deduced that the phenylacetyl moiety in legonoxamine A may have contributed significantly to its enhanced potency. Our findings contribute to the growing library of Streptomyces-derived metabolites and underscore the genus' potential as a promising source of lead compounds.

Remediation of the NMR data of natural glycans

Primary structure elucidation in glycobiology is strongly affected by published structure-reporting NMR signals, especially on the 13C nucleus. The glycan NMR simulation accuracy and machine learning outcome depend on the quality of the NMR signal assignment in glycan databases. Within our work on improving the data quality in the Carbohydrate Structure Database (CSDB), we have applied a systematic search for inconsistencies in the published NMR data. The search was based on a bulk comparison between the experimental and simulated 13C NMR chemical shifts and manual analysis of the mismatches. On the basis of this analysis, CSDB was remediated by marking and correcting the NMR errors found in 272 structure elucidation reports published over the past 40 years.

Accraspiroketides A-B, Phenylnaphthacenoid-Derived Polyketides with Unprecedented [6 + 6+6 + 6] + [5 + 5] Spiro-Architecture

Two novel polyketides, accraspiroketides A (1) and B (2), which feature unprecedented [6 + 6+6 + 6] + [5 + 5] spiro chemical architectures, were isolated from Streptomyces sp. MA37 ΔaccJ mutant strain. Compounds 1-2 exhibit excellent activity against Gram-positive bacteria (MIC = 1.5-6.3 μg/mL). Notably, 1 and 2 have superior activity against clinically isolated Enterococcus faecium K60-39 (MIC = 4.0 μg/mL and 4.7 μg/mL, respectively) than ampicillin (MIC = 25 μg/mL).

Machine learning-assisted structure annotation of natural products based on MS and NMR data

Covering: up to March 2023Machine learning (ML) has emerged as a popular tool for analyzing the structures of natural products (NPs). This review presents a summary of the recent advancements in ML-assisted mass spectrometry (MS) and nuclear magnetic resonance (NMR) data analysis to establish the chemical structures of NPs. First, ML-based MS/MS analyses that rely on library matching are discussed, which involves the utilization of ML algorithms to calculate similarity, predict the MS/MS fragments, and form molecular fingerprint. Then, ML assisted MS/MS structural annotation without library matching is reviewed. Furthermore, the cases of ML algorithms in assisting structural studies of NPs based on NMR are discussed from four perspectives: NMR prediction, functional group identification, structural categorization and quantum chemical calculation. Finally, the review concludes with a discussion of the challenges and the trends associated with the structural establishment of NPs based on ML algorithms.

Relative stereochemical determination of the C61-C83 fragment of symbiodinolide using a stereodivergent synthetic approach

Structural determination is required in the use of marine natural products to create novel drugs and drug leads in medicinal chemistry. Symbiodinolide, which is a polyol marine natural product with a molecular weight of 2860, increases the intracellular Ca2+ concentration and exhibits inhibitory activity against cyclooxygenase-1. Seventy percent of the structure of symbiodinolide has been stereochemically clarified. Herein, we report the elucidation of the relative configuration of the C61-C83 fragment, which is among the remaining thirty percent, using a stereodivergent synthetic strategy. We first assigned the relative configuration of the C61-C74 fragment. Two candidate diastereomers of the C61-C74 fragment were synthesized, and their NMR data were compared with those of the natural product, revealing the relative stereochemistry of this component. We then narrowed down the candidate compounds for the C69-C83 fragment from 16 possible diastereomers by analyzing the NMR data of the natural product, and we thus selected eight candidate diastereomers. Stereodivergent synthesis of the candidates for this fragment and comparison of the NMR data of the natural product and the eight synthetic products resulted in the relative stereostructural clarification of the C69-C83 fragment. These individually determined relative stereochemistries of the C61-C74 and C69-C83 fragments were connected via the common C69-C73 tetrahydropyran moiety of the fragments. Finally, the relative configuration of the C61-C83 fragment of symbiodinolide was determined. The stereodivergent synthetic approach used in this study can be extended to the stereochemical determination of other fragments of symbiodinolide.

Enhancing Efficiency of Natural Product Structure Revision: Leveraging CASE and DFT over Total Synthesis

Natural products remain one of the major sources of coveted, biologically active compounds. Each isolated compound undergoes biological testing, and its structure is usually established using a set of spectroscopic techniques (NMR, MS, UV-IR, ECD, VCD, etc.). However, the number of erroneously determined structures remains noticeable. Structure revisions are very costly, as they usually require extensive use of spectroscopic data, computational chemistry, and total synthesis. The cost is particularly high when a biologically active compound is resynthesized and the product is inactive because its structure is wrong and remains unknown. In this paper, we propose using Computer-Assisted Structure Elucidation (CASE) and Density Functional Theory (DFT) methods as tools for preventive verification of the originally proposed structure, and elucidation of the correct structure if the original structure is deemed to be incorrect. We examined twelve real cases in which structure revisions of natural products were performed using total synthesis, and we showed that in each of these cases, time-consuming total synthesis could have been avoided if CASE and DFT had been applied. In all described cases, the correct structures were established within minutes of using the originally published NMR and MS data, which were sometimes incomplete or had typos.

Bridging Chemical Knowledge and Machine Learning for Performance Prediction of Organic Synthesis

Recent years have witnessed a boom of machine learning (ML) applications in chemistry, which reveals the potential of data-driven prediction of synthesis performance. Digitalization and ML modelling are the key strategies to fully exploit the unique potential within the synergistic interplay between experimental data and the robust prediction of performance and selectivity. A series of exciting studies have demonstrated the importance of chemical knowledge implementation in ML, which improves the model's capability for making predictions that are challenging and often go beyond the abilities of human beings. This Minireview summarizes the cutting-edge embedding techniques and model designs in synthetic performance prediction, elaborating how chemical knowledge can be incorporated into machine learning until June 2022. By merging organic synthesis tactics and chemical informatics, we hope this Review can provide a guide map and intrigue chemists to revisit the digitalization and computerization of organic chemistry principles.

Furaquinocins K and L: Novel Naphthoquinone-Based Meroterpenoids from Streptomyces sp. Je 1-369

Actinomycetes are the most prominent group of microorganisms that produce biologically active compounds. Among them, special attention is focused on bacteria in the genus Streptomyces. Streptomycetes are an important source of biologically active natural compounds that could be considered therapeutic agents. In this study, we described the identification, purification, and structure elucidation of two new naphthoquinone-based meroterpenoids, furaquinocins K and L, from Streptomyces sp. Je 1-369 strain, which was isolated from the rhizosphere soil of Juniperus excelsa (Bieb.). The main difference between furaquinocins K and L and the described furaquinocins was a modification in the polyketide naphthoquinone skeleton. In addition, the structure of furaquinocin L contained an acetylhydrazone fragment, which is quite rare for natural compounds. We also identified a furaquinocin biosynthetic gene cluster in the Je 1-369 strain, which showed similarity (60%) with the furaquinocin B biosynthetic gene cluster from Streptomyces sp. KO-3988. Furaquinocin L showed activity against Gram-positive bacteria without cytotoxic effects.

Trichopsistides A and B: Two Highly Oxygenated Pentacyclic Polyketides with Promising Inhibitory Effects on the NF-κB Signaling Pathway from the Fungus Trichoderma koningiopsis WZ-196

Two highly oxygenated pentacyclic polyketides with two new carbon skeletons, trichopsistide A (1) and trichopsistide B (2), were isolated from the plant endophyte Trichoderma koningiopsis WZ-196 derived from the leaf of Rubia podantha Diels. The structures of these polyketides with full configurations were determined by comprehensive spectroscopic analysis, computer-assisted structure elucidation software, computational calculation, and X-ray crystal diffraction. Among them, 1 represented the first example of an unprecedented 5/6/6/6/5 pentacyclic ketal-containing polyketide pyridine alkaloid, and 2 possessed a novel 6/6/6/6/5 pentacyclic ketal-containing polyketide scaffold fused with an α-pyrone. The plausible biosynthetic route for 1 and 2 was also proposed. Moreover, biological activity assays showed that 1 and 2 possessed inhibitory effects on the NF-κB signaling pathway with IC₅₀ values of 14.77 and 8.58 μM, respectively. Furthermore, 1 and 2 could also inhibit the expression of IκBα and p65 phosphorylation, decrease the expression of MCP-1, E-selectin, and IL-8 at the mRNA level, and inhibit the TNF-α-induced nuclear translocation of p65.

Peculiar Reaction Products and Mechanisms Revisited with Machine Learning-Augmented Computational NMR

DU8ML, a fast and accurate machine learning-augmented density functional theory (DFT) method for computing nuclear magnetic resonance (NMR) spectra, proved effective for high-throughput revision of misassigned natural products. In this paper, we disclose another important aspect of its application: correction of unusual reaction mechanisms originally proposed because of incorrect product structures.

Pitfalls in the structural elucidation of small molecules. A critical analysis of a decade of structural misassignments of marine natural products

Covering: July 2010 to August 2021This article summarizes more than 200 cases of misassigned marine natural products reported between July 2010 and August 2021, sorting out errors according to the structural elements. Based on a comparative analysis of the original and the revised structures, major pitfalls still plaguing the structural elucidation of small molecules were identified, emphasizing the role of total synthesis, crystallography, as well as chemical- and biosynthetic logic to complement spectroscopic data. Distinct "trends" in natural product misassignment are evident between compounds of marine and plant origin, with an overall much lower incidence of "impossible" structures within misassigned marine natural products.

DU8ML: Machine Learning-Augmented Density Functional Theory Nuclear Magnetic Resonance Computations for High-Throughput In Silico Solution Structure Validation and Revision of Complex Alkaloids

Machine learning (ML) profoundly improves the accuracy of the fast DU8+ hybrid density functional theory/parametric computations of nuclear magnetic resonance spectra, allowing for high throughput in silico validation and revision of complex alkaloids and other natural products. Of nearly 170 alkaloids surveyed, 35 structures are revised with the next-generation ML-augmented DU8 method, termed DU8ML.

Phaeosphspirone (1/1'), a pair of unique polyketide enantiomers with an unusual 6/5/5/6 tetracyclic ring from the desert plant endophytic fungus Phaeosphaeriaceae sp

Phaeosphspirone, an undescribed polyketide with a unique 6/5/5/6-fused tetracyclic system, and two known analogues, herbarin and O-methylherbarin, were purified from the endophytic fungus Phaeosphaeriaceae sp. isolated from the desert plant Bassia dasyphylla. The connectivity and relative configuration of phaeosphspirone was elucidated by comprehensive HR-ESI-MS and NMR analysis together with a computer-assisted structure elucidation (CASE) method. A pair of enantiomers existing in phaeosphspirone were separated by HPLC chromatography after reacting with chiral reagents, from which the absolute configuration of phaeosphspirone was simultaneously determined based on Mosher's rule. This tandem strategy provides a useful approach for the separation and stereochemical determination of enantiomers possessing secondary hydroxyl groups. The structural feature of phaeosphspirone, herbarin and O-methylherbarin together with gene cluster analysis suggested their polyketide biosynthetic origin. Herbarin and O-methylherbarin exhibited moderate cytotoxicity against three cancer cell lines.

Assigning the stereochemical structures of aurantinin A and B with the assistance of biosynthetic investigations

The stereochemistry of aurantinin was determined by spectroscopic and computational analysis with the assistance of biosynthetic studies. The latter method provided critical evidence for the assignment of the configuration of the 3-ketosugar moiety.

Sampling CASE Application for the Quality Control of Published Natural Product Structures

Structure elucidation with NMR correlation data is dicey, as there is no way to tell how ambiguous the data set is and how reliably it will define a constitution. Many different software tools for computer assisted structure elucidation (CASE) have become available over the past decades, all of which could ensure a better quality of the elucidation process, but their use is still not common. Since 2011, WebCocon has integrated the possibility to generate theoretical NMR correlation data, starting from an existing structural proposal, allowing this theoretical data then to be used for CASE. Now, WebCocon can also read the recently presented NMReDATA format, allowing for uncomplicated access to CASE with experimental data. With these capabilities, WebCocon presents itself as an easily accessible Web-Tool for the quality control of proposed new natural products. Results of this application to several molecules from literature are shown and demonstrate how CASE can contribute to improve the reliability of Structure elucidation with NMR correlation data.

Parallel NMR Supersequences: Ten Spectra in a Single Measurement

The principles employed in parallel NMR and MRI are applied to NMR supersequences yielding as many as ten 2D NMR spectra in one measurement. We present a number of examples where two NOAH (NMR by Ordered Acquisition using 1H-detection) supersequences are recorded in parallel, thus dramatically increasing the information content obtained in a single NMR experiment. The two parallel supersequences entangled by time-sharing schemes (IPAP-seHSQC, HSQC-COSY, and HSQC-TOCSY) incorporate also modified (sequential and/or interleaved) conventional pulse schemes (modules), including HMBC, TOCSY, COSY, CLIP-COSY, NOESY, and ROESY. Such parallel supersequences can be tailored for specific applications, for instance, the analysis and characterization of molecular structure of complex organic molecules from a single measurement. In particular, the CASPER software was used to establish the structure of a tetrasaccharide, β-LNnTOMe, with a high degree of confidence from a single measurement involving a parallel NOAH-5 supersequence.

ACD/Structure Elucidator: 20 Years in the History of Development

The first methods associated with the Computer-Assisted Structure Elucidation (CASE) of small molecules were published over fifty years ago when spectroscopy and computer science were both in their infancy. The incredible leaps in both areas of technology could not have been envisaged at that time, but both have enabled CASE expert systems to achieve performance levels that in their present state can outperform many scientists in terms of speed to solution. The computer-assisted analysis of enormous matrices of data exemplified 1D and 2D high-resolution NMR spectroscopy datasets can easily solve what just a few years ago would have been deemed to be complex structures. While not a panacea, the application of such tools can provide support to even the most skilled spectroscopist. By this point the structures of a great number of molecular skeletons, including hundreds of complex natural products, have been elucidated using such programs. At this juncture, the expert system ACD/Structure Elucidator is likely the most advanced CASE system available and, being a commercial software product, is installed and used in many organizations. This article will provide an overview of the research and development required to pursue the lofty goals set almost two decades ago to facilitate highly automated approaches to solving complex structures from analytical spectroscopy data, using NMR as the primary data-type.

Structural Revisions of Two Highly Aromatic Naphthoquinone-Derived Dimers Based on NMR Analysis, Computer-Assisted Structure Elucidation Methods, and Computations

Eleucanainones A and B are two structurally complex naphthoquinone-derived dimers whose structure identification is difficult. Large yellow fragments of the preliminary CASE (computer-assisted structure elucidation) analysis revealed that the original structures might be questionable. Structural revisions of the two compounds were proposed on the basis of NMR analysis, CASE methods, conformation analysis, and DFT (density functional theory) NMR calculations with a custom DP4+ analysis. In addition, a polyketide-folded biosynthetic pathway of the two revised structures was proposed.

Incorporation of 4J-HMBC and NOE Data into Computer-Assisted Structure Elucidation with WebCocon

Over the past decades, different software programs have been developed for the Computer-Assisted Structure Elucidation (CASE) with NMR data using with various approaches. WebCocon is one of them that has been continuously improved over the past 20 years. Here, we present the inclusion of 4J_CH correlations (4J-HMBC) in the HMBC interpretation of Cocon and NOE data in WebCocon. The 4J-HMBC data is used during the structure generation process, while the NOE data is used in post-processing of the results. The marine natural product oxocyclostylidol was selected to demonstrate WebCocon’s enhanced HMBC data processing capabilities. A systematic study of the 4J_CH correlations of oxocyclostylidol was performed. The application of NOEs in CASE is demonstrated using the NOE correlations of the diterpene pyrone asperginol A known from the literature. As a result, we obtained a conformation that corresponds very well to the existing X-ray structure.

Computer Assisted Structure Elucidation (CASE): Current and future perspectives

The first efforts for the development of methods for Computer-Assisted Structure Elucidation (CASE) were published more than 50 years ago. CASE expert systems based on one-dimensional (1D) and two-dimensional (2D) Nuclear Magnetic Resonance (NMR) data have matured considerably by now. The structures of a great number of complex natural products have been elucidated and/or revised using such programs. In this article, we discuss the most likely directions in which CASE will evolve. We act on the premise that a synergistic interaction exists between CASE, new NMR experiments, and methods of computational chemistry, which are continuously being improved. The new developments in NMR experiments (long-range correlation experiments, pure-shift methods, coupling constants measurement and prediction, residual dipolar couplings [RDCs]), and residual chemical shift anisotropies [RCSAs], evolution of density functional theory (DFT), and machine learning algorithms will have an influence on CASE systems and vice versa. This is true also for new techniques for chemical analysis (Atomic Force Microscopy [AFM], "crystalline sponge" X-ray analysis, and micro-Electron Diffraction [micro-ED]), which will be used in combination with expert systems. We foresee that CASE will be utilized widely and become a routine tool for NMR spectroscopists and analysts in academic and industrial laboratories. We believe that the "golden age" of CASE is still in the future.

Dermacozine N, the First Natural Linear Pentacyclic Oxazinophenazine with UV-Vis Absorption Maxima in the Near Infrared Region, along with Dermacozines O and P Isolated from the Mariana Trench Sediment Strain Dermacoccus abyssi MT 1.1T

Three dermacozines, dermacozines N-P (1-3), were isolated from the piezotolerant Actinomycete strain Dermacoccus abyssi MT 1.1T, which was isolated from a Mariana Trench sediment in 2006. Herein, we report the elucidation of their structures using a combination of 1D/2D NMR, LC-HRESI-MSn, UV-Visible, and IR spectroscopy. Further confirmation of the structures was achieved through the analysis of data from density functional theory (DFT)-UV-Visible spectral calculations and statistical analysis such as two tailed t-test, linear regression-, and multiple linear regression analysis applied to either solely experimental or to experimental and calculated 13C-NMR chemical shift data. Dermacozine N (1) bears a novel linear pentacyclic phenoxazine framework that has never been reported as a natural product. Dermacozine O (2) is a constitutional isomer of the known dermacozine F while dermacozine P (3) is 8-benzoyl-6-carbamoylphenazine-1-carboxylic acid. Dermacozine N (1) is unique among phenoxazines due to its near infrared (NIR) absorption maxima, which would make this compound an excellent candidate for research in biosensing chemistry, photodynamic therapy (PDT), opto-electronic applications, and metabolic mapping at the cellular level. Furthermore, dermacozine N (1) possesses weak cytotoxic activity against melanoma (A2058) and hepatocellular carcinoma cells (HepG2) with IC50 values of 51 and 38 μM, respectively.

Quantum Chemistry Calculations for Metabolomics

A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for "standards-free" identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.

Minimizing the risk of deducing wrong natural product structures from NMR data

There continues to be a disturbing number of natural products reported in the literature whose structures are incorrect. At least in part, this reflects the fact that many natural product chemists have limited formal nuclear magnetic resonance training. Gaps in training and lack of awareness regarding the challenges and ambiguities associated with two-dimensional nuclear magnetic resonance data interpretation can easily lead to errors in structure elucidation. The purpose of this tutorial is to point out some of these issues, highlight the kinds of errors that have been made and provide specific advice on how to avoid these missteps such that the risk of reporting a wrong structure is minimized.

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.

Two new seco-polycyclic polyprenylated acylphloroglucinol from Hypericum sampsonii

Two rare seco-polycyclic polyprenylated acylphloroglucinols (1 and 2) were isolated from Hypericum sampsonii. Compounds 1 and 2 showed moderate multidrug resistance (MDR) reversal activity to resistant cancer cells, HepG2/ADR and MCF-7/ADR.

Natural potential neuroinflammatory inhibitors from Stephania epigaea H.S. Lo

Stephania epigaea H. S. Lo is a folk medicine widely distributed in the south of China, especially in Yunnan and Guangxi province. An in vitro anti-neuroinflammatory study showed that total alkaloids of it can potently inhibit LPS-induced NO releasing of BV2 cells with an IC₅₀ value of 10.05 ± 2.03 μg/mL (minocycline as the positive drug, IC₅₀ 15.49 ± 2.14 μM). The phytochemical investigation of the total alkaloids afforded three new phenanthrene (1-3), two lactams (4a, 4b), and nine aporphine derivatives (5-13). The final structure of 1 was identified by computer-assisted structure elucidation (ACD/Structure Elucidator software and the ¹³C NMR calculation with GIAO method) due to many possibilities of the substituent pattern. All isolates were evaluated for their anti-neuroinflammatory effects, and as a result, 5, 8, 10, and 11 exhibited stronger inhibitory activities than the minocycline. The results suggested S. epigaea could provide potential therapeutic agents for neurodegenerative diseases.

Total synthesis and complete configurational assignment of amphirionin-2

Amphirionin-2 is a linear polyketide metabolite that exhibits potent and selective cytotoxic activity against certain human cancer cell lines. We disclose herein the first total synthesis of amphirionin-2 and determination of its absolute configuration. Our synthesis featured an extensive use of cobalt-catalyzed Mukaiyama-type cyclization of γ-hydroxy olefins for stereoselective formation of all the tetrahydrofuran rings found in the natural product, and a late-stage Stille-type coupling for convergent assembly of the entire carbon backbone. Four candidate diastereomers of amphirionin-2 were synthesized in a unified, convergent manner, and their spectroscopic/chromatographic properties were compared with those of the authentic material. The present study culminated in the reassignment of the C5/C7 relative configuration, assignment of the C12/C18 relative configuration, and determination of the absolute configuration of amphirionin-2.

Reconsidering the Structure of Serlyticin-A

Serlyticin-A is a secondary metabolite first isolated from a culture of Serratia ureilytica grown using squid pen as the sole carbon/nitrogen source. A previous study by Kuo et al. demonstrated that it has antioxidative and antiproliferative properties. However, the proposed chemical structure of serlyticin-A is likely incorrect based on the thermodynamic instability of its three contiguous heteroatom-heteroatom bonds. Here, we use quantum chemical calculations to predict 1H and 13C chemical shifts for serlyticin-A and demonstrate a discrepancy between the calculated and experimental chemical shifts. We then propose several reasonable alternative structures for serlyticin-A. Considering the known antioxidant and antiproliferative activity of hydroxamic acids as well as their stability and prevalence in natural products of bacterial origin, we believe that serlyticin-A is most likely 3-indolylacetohydroxamic acid (4). We provide our rationale for this assignment as well as experimental data for pure 3-indolylacetohydroxamic acid obtained via de novo synthesis. This study highlights the power of computational NMR shift prediction to revise chemical structures for natural products like serlyticin-A.

Computational methods for NMR and MS for structure elucidation I: software for basic NMR

Structure elucidation is an important and sometimes time-consuming step for natural products research. This step has evolved in the past few years to a faster and more automated process due to the development of several computational programs and analytical techniques. In this paper, the topics of NMR prediction and CASE programs are addressed. Furthermore, the elucidation of natural peptides is discussed.

Computationally-assisted discovery and structure elucidation of natural products

Computer hardware development coupled with the development of quantum chemistry, new computational models and algorithms, and user-friendly interfaces have lowered the barriers to the use of computation in the discovery and structure elucidation of natural products. Consequently, the use of computational chemistry software as a tool to discover and determine the structure of natural products has become more common in recent years. In this review, we provide several examples of recent studies that used computer technology to facilitate the discovery and structure determination of various natural products.

LC-HRMS-Database Screening Metrics for Rapid Prioritization of Samples to Accelerate the Discovery of Structurally New Natural Products

In order to accelerate the isolation and characterization of structurally new or novel secondary metabolites, it is crucial to develop efficient strategies that prioritize samples with greatest promise early in the workflow so that resources can be utilized in a more efficient and cost-effective manner. We have developed a metrics-based prioritization approach using exact LC-HRMS, which uses data for 24 618 marine natural products held in the PharmaSea database. Each sample was evaluated and allocated a metric score by a software algorithm based on the ratio of new masses over the total (sample novelty), ratio of known masses over the total (chemical novelty), number of peaks above a defined peak area threshold (sample complexity), and peak area (sample diversity). Samples were then ranked and prioritized based on these metric scores. To validate the approach, eight marine sponges and six tunicate samples collected from the Fiji Islands were analyzed, metric scores calculated, and samples targeted for isolation and characterization of new compounds. Structures of new compounds were elucidated by spectroscopic techniques, including 1D and 2D NMR, MS, and MS/MS. Structures were confirmed by computer-assisted structure elucidation methods (CASE) using the ACD/Structure Elucidator Suite.

The role of computer-assisted structure elucidation (CASE) programs in the structure elucidation of complex natural products

Computer-assisted structure elucidation can help to determine the structures of complex natural products while minimizing the risk of structure errors.

NMReDATA, a standard to report the NMR assignment and parameters of organic compounds

Even though NMR has found countless applications in the field of small molecule characterization, there is no standard file format available for the NMR data relevant to structure characterization of small molecules. A new format is therefore introduced to associate the NMR parameters extracted from 1D and 2D spectra of organic compounds to the proposed chemical structure. These NMR parameters, which we shall call NMReDATA (for nuclear magnetic resonance extracted data), include chemical shift values, signal integrals, intensities, multiplicities, scalar coupling constants, lists of 2D correlations, relaxation times, and diffusion rates. The file format is an extension of the existing Structure Data Format, which is compatible with the commonly used MOL format. The association of an NMReDATA file with the raw and spectral data from which it originates constitutes an NMR record. This format is easily readable by humans and computers and provides a simple and efficient way for disseminating results of structural chemistry investigations, allowing automatic verification of published results, and for assisting the constitution of highly needed open-source structural databases.

Structural Revisions in Natural Ellagitannins

Ellagitannins are literally a class of tannins. Triggered by the oxidation of the phenolic parts on β-pentagalloyl-d-glucose, ellagitannins are generated through various structural conversions, such as the coupling of the phenolic parts, oxidation to highly complex structures, and the formation of dimer and lager analogs, which expand the structural diversity. To date, more than 1000 natural ellagitannins have been identified. Since these phenolic compounds exhibit a variety of biological activities, ellagitannins have potential applications in medicine and health enhancement. Within the context of identifying suitable applications, considerations need to be based on correct structural features. This review describes the structural revisions of 32 natural ellagitannins, namely alnusiin; alnusnin A and B; castalagin; castalin; casuarinin; cercidinin A and B; chebulagic acid; chebulinic acid; corilagin; geraniin; isoterchebin; nobotanin B, C, E, G, H, I, J, and K; punicalagin; punicalin; punigluconin; roxbin B; sanguiin H-2, H-3, and H-6; stachyurin; terchebin; vescalagin; and vescalin. The major focus is on the outline of the initial structural determination, on the processes to find the errors in the structure, and on the methods for the revision of the structure.

Targeted Dereplication of Microbial Natural Products by High-Resolution MS and Predicted LC Retention Time

A new strategy for the identification of known compounds in Streptomyces extracts that can be applied in the discovery of natural products is presented. The strategy incorporates screening a database of 5555 natural products including 5098 structures from Streptomyces sp., using a high-throughput LCMS data processing algorithm that utilizes HRMS data and predicted LC retention times (t_R) as filters for rapid identification of known compounds in the natural product extract. The database, named StrepDB, contains for each compound the structure, molecular formula, molecular mass, and predicted LC retention time. All identified compounds are annotated and color coded for easier visualization. It is an indirect approach to quickly assess masses (which are not annotated) that may potentially lead to the discovery of new or novel structures. In addition, a spectral database named MbcDB was generated using the ACD/Spectrus DB Platform. MbcDB contains 665 natural products, each with structure, experimental HRESIMS, MS/MS, UV, and NMR spectra. StrepDB was used to screen a mutant Streptomyces albus extract, which led to the identification and isolation of two new compounds, legonmaleimides A and B, the structures of which were elucidated with the aid of MbcDB and spectroscopic techniques. The structures were confirmed by computer-assisted structure elucidation (CASE) methods using ACD/Structure Elucidator Suite. The developed methodology suggests a pipeline approach to the dereplication of extracts and discovery of novel natural products.

High-Throughput in Silico Structure Validation and Revision of Halogenated Natural Products Is Enabled by Parametric Corrections to DFT-Computed 13C NMR Chemical Shifts and Spin-Spin Coupling Constants

Halogenated natural products constitute diverse and promising feedstock for molecular pharmaceuticals. However, their solution-structure elucidation by NMR presents several challenges, including the lack of fast methods to compute ¹³C chemical shifts for carbons bearing heavy atoms. We show that parametric corrections to DFT-computed chemical shifts in conjunction with rff-computed spin-spin coupling constants allow for fast and reliable screening of a large number of reported halogenated natural products, resulting in expedient structure validation or revision. In this paper, we examine more than 100 structures of halogenated terpenoids and other natural products with the new parametric approach and demonstrate that the accuracy of the combined method is sufficient to identify misassignments and suggest revisions in most cases (16 structures are revised). As the 1D ¹H and ¹³C NMR data are ubiquitous and most routinely used in solution structure elucidation, this fast and efficient two-criterion method (nuclear spin-spin coupling and ¹³C chemical shifts) which we term DU8+ is recommended as the first essential step in structure assignment and validation.

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

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

A NMR method for relative stereochemical assignments of the tricyclic core of cephalosporolides, penisporolides and related synthetic analogues

A new NMR method is developed to discriminate the four possible diastereomeric SAFLs, leading to revisions of 11 synthetic compounds.

The importance of asking “how and why?” in natural product structure elucidation

This review highlights why careful consideration of the biosynthetic origin (the how) and the biological function (the why) of a natural product can be so useful during the determination of its structure.

A Critical Evaluation of the Quality of Published 13C NMR Data in Natural Product Chemistry

Nuclear Magnetic Resonance spectroscopy contributes very efficiently to the structure elucidation process in organic chemistry. Carbon-13 NMR spectroscopy allows direct insight into the skeleton of organic compounds and therefore plays a central role in the structural assignment of natural products. Despite this important contribution, there is no established and well-accepted workflow protocol utilized during the first steps of interpreting spectroscopic data and converting them into structural fragments and then combining them, by considering the given spectroscopic constraints, into a final proposal of structure. The so-called "combinatorial explosion" in the process of structure generation allows in many cases the generation of reasonable alternatives, which are usually ignored during manual interpretation of the measured data leading ultimately to a large number of structural revisions. Furthermore, even when the determined structure is correct, problems may exist such as assignment errors, ignoring chemical shift values, or assigning lines of impurities to the compound under consideration. An extremely large heterogeneity in the presentation of carbon NMR data can be observed, but, as a result of the efficiency and precision of spectrum prediction, the published data can be analyzed in substantial detail.This contribution presents a comprehensive analysis of frequently occurring errors with respect to ¹³C NMR spectroscopic data and proposes a straightforward protocol to eliminate a high percentage of the most obvious errors. The procedure discussed can be integrated readily into the processes of submission and peer-reviewing of manuscripts.