Structure elucidation of complex natural products and new organic compounds remains a challenging problem. To support this endeavor, CASE (computer-assisted structure elucidation) expert systems were developed. These systems are capable of generating a set of all possible structures consistent with an ensemble of 2D NMR data followed by selection of the most probable structure on the basis of empirical NMR chemical shift prediction. However, in some cases, empirical chemical shift prediction is incapable of distinguishing the correct structure. Herein, we demonstrate for the first time that the combination of CASE and density functional theory (DFT) methods for NMR chemical shift prediction allows the determination of the correct structure even in difficult situations. An expert system, ACD/Structure Elucidator, was used for the CASE analysis. This approach has been tested on three challenging natural products: aquatolide, coniothyrione, and chiral epoxyroussoenone. This work has demonstrated that the proposed synergistic approach is an unbiased, reliable, and very efficient structure verification and de novo structure elucidation method that can be applied to difficult structural problems when other experimental methods would be difficult or impossible to use.
Click hFew secondary metabolites have been reported from mammalian microbiome bacteria despite the large numbers of diverse taxa that inhabit warm-blooded higher vertebrates. As a means to investigate natural products from these microorganisms, an opportunistic sampling protocol was developed, which focused on exploring bacteria isolated from roadkill mammals. This initiative was made possible through the establishment of a newly created discovery pipeline, which couples laser ablation electrospray ionization mass spectrometry (LAESIMS) with bioassay testing, to target biologically active metabolites from microbiome-associated bacteria. To illustrate this process, this report focuses on samples obtained from the ear of a roadkill opossum (Dideiphis virginiana) as the source of two bacterial isolates (Pseudomonas sp. and Serratia sp.) that produced several new and known cyclic lipodepsipeptides (viscosin and serrawettins, respectively). These natural products inhibited biofilm formation by the human pathogenic yeast Candida albicans at concentrations well below those required to inhibit yeast viability. Phylogenetic analysis of 16S rRNA gene sequence libraries revealed the presence of diverse microbial communities associated with different sites throughout the opossum carcass. A putative biosynthetic pathway responsible for the production of the new serrawettin analogues was identified by sequencing the genome of the Serratia sp. isolate. This study provides a functional roadmap to carrying out the systematic investigation of the genomic, microbiological, and chemical parameters related to the production of natural products made by bacteria associated with non-anthropoidal mammalian microbiomes. Discoveries emerging from these studies are anticipated to provide a working framework for efforts aimed at augmenting microbiomes to deliver beneficial natural products to a host.ere to edit the content
To identify natural bioactive compounds from complex mixtures such as plant extracts, efficient fractionation for biological screening is mandatory. In this context, a fully automated workflow based on two-dimensional liquid chromatography (2D-LC × LC) was developed, allowing for the production of hundreds of semipure fractions per extract. Moreover, the ELSD response was used for online sample weight estimation and automated concentration normalization for subsequent bioassays. To evaluate the efficiency of this protocol, an enzymatic assay was developed using AMP-activated protein kinase (AMPK). The activation of AMPK by nonactive extracts spiked with biochanin A, a known AMPK activator, was enhanced greatly when the fractionation workflow was applied compared to screening crude spiked extracts. The performance of the workflow was further evaluated on a red clover (Trifolium pratense) extract, which is a natural source of biochanin A. In this case, while the crude extract or 1D chromatography fractions failed to activate AMPK, semipure fractions containing biochanin A were readily localized when produced by the 2D-LC×LC-ELSD workflow. The automated fractionation methodology presented demonstrated high efficiency for the detection of bioactive compounds at low abundance in plant extracts for high-throughput screening. This procedure can be used routinely to populate natural product libraries for biological screening.
Centrifugal partition chromatography (CPC) and all countercurrent separation apparatus provide chemists with efficient ways to work with complex matrixes, especially in the domain of natural products. However, despite the great advances provided by these techniques, more efficient ways of analyzing the output flow would bring further enhancement. This study describe a hyphenated approach made by coupling NMR with CPC through a hybrid-indirect coupling made possible by using a solid phase extraction (SPE) apparatus intended for high-pressure liquid chromatography (HPLC)-NMR hyphenation. Some hardware changes were needed to adapt the incompatible flow-rates and a reverse-engineering approach that led to the specific software required to control the apparatus. 1D 1HNMR and 1H–1H correlation spectroscopy (COSY) spectra were acquired in reasonable time without the need for any solvent-suppression method thanks to the SPE nitrogen drying step. The reduced usage of expensive deuterated solvents from several hundreds of milliliters to the milliliter order is the major improvement of this approach compared to the previously published ones.
The sugar subunits of natural glycosides can be conveniently determined by acid hydrolysis and 1H NMR spectroscopy without isolation or derivatization. The chemical shifts, coupling constants, and integral ratios of the anomeric signals allow each monosaccharide to be identified and its molar ratio to other monosaccharides to be quantified. The NMR data for the anomeric signals of 28 monosaccharides and three disaccharides are reported. Application of the method is demonstrated with the flavonoid glycoside naringin (1), the aminoglycoside antibiotics kanamycin (2) and tobramycin (3), and the saponin digitonin (4).
Analysis of a single analyte by mass spectrometry can result in the detection of more than 100 degenerate peaks. These degenerate peaks complicate spectral interpretation and are challenging to annotate. In mass spectrometry-based metabolomics, this degeneracy leads to inflated false discovery rates, data sets containing an order of magnitude more features than analytes, and an inefficient use of resources during data analysis. Although software has been introduced to annotate spectral degeneracy, current approaches are unable to represent several important classes of peak relationships. These include heterodimers and higher complex adducts, distal fragments, relationships between peaks in different polarities, and complex adducts between features and background peaks. Here we outline sources of peak degeneracy in mass spectra that are not annotated by current approaches and introduce a software package called mz.unity to detect these relationships in accurate mass data. Using mz.unity, we find that data sets contain many more complex relationships than we anticipated. Examples include the adduct of glutamate and nicotinamide adenine dinucleotide (NAD), fragments of NAD detected in the same or opposite polarities, and the adduct of glutamate and a background peak. Further, the complex relationships we identify show that several assumptions commonly made when interpreting mass spectral degeneracy do not hold in general. These contributions provide new tools and insight to aid in the annotation of complex spectral relationships and provide a foundation for improved data set identification. Mz.unity is an R package and is freely available at https://github.com/nathaniel-mahieu/mz.unity as well as our laboratory Web site http://pattilab.wustl.edu/software/.
The Research Ideas and Outcomes (RIO) journal publishes all outputs of the research cycle, including: project proposals, data, methods, workflows, software, project reports and research articles together on a single collaborative platform, with the most transparent, open and public peer-review process. Our scope encompasses all areas of academic research, including science, technology, humanities and the social sciences.
Previously, we showed a few examples of preparing crude extracts from plants and other organisms. While sometimes (rarely) we get lucky and obtain an extract that is predominantly one compound, a more representative situation is that a mixture of compounds is obtained.
Excellent website MOC (Master Organic Chemistry) sums up some of Natural Products isolations techniques ... perfect for students ! Check out the crystal glamour shots !
The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.
After several years of development, and of outstanding applications by the community, the GNPS paper is finally out. A milestone, for Mass Spec in Natural Products Chemistry and Metabolomics. More than 13,000 users worldwide.
We describe a tool, competitive fragmentation modeling for electron ionization (CFM-EI) that, given a chemical structure (e.g., in SMILES or InChI format), computationally predicts an electron ionization mass spectrum (EI-MS) (i.e., the type of mass spectrum commonly generated by gas chromatography mass spectrometry). The predicted spectra produced by this tool can be used for putative compound identification, complementing measured spectra in reference databases by expanding the range of compounds able to be considered when availability of measured spectra is limited. The tool extends CFM-ESI, a recently developed method for computational prediction of electrospray tandem mass spectra (ESI-MS/MS), but unlike CFM-ESI, CFM-EI can handle odd-electron ions and isotopes and incorporates an artificial neural network. Tests on EI-MS data from the NIST database demonstrate that CFM-EI is able to model fragmentation likelihoods in low-resolution EI-MS data, producing predicted spectra whose dot product scores are significantly better than full enumeration “bar-code” spectra. CFM-EI also outperformed previously reported results for MetFrag, MOLGEN-MS, and Mass Frontier on one compound identification task. It also outperformed MetFrag in a range of other compound identification tasks involving a much larger data set, containing both derivatized and nonderivatized compounds. While replicate EI-MS measurements of chemical standards are still a more accurate point of comparison, CFM-EI’s predictions provide a much-needed alternative when no reference standard is available for measurement. CFM-EI is available at https://sourceforge.net/projects/cfm-id/ for download and http://cfmid.wishartlab.com as a web service.
The determination of the molecular formula is one of the earliest and most important steps when investigating the chemical nature of an unknown compound. Common approaches use the isotopic pattern of a compound measured using mass spectrometry. Computational methods to determine the molecular formula from this isotopic pattern require a fixed set of elements. Considering all possible elements severely increases running times and more importantly the chance for false positive identifications as the number of candidate formulas for a given target mass rises significantly if the constituting elements are not prefiltered. This negative effect grows stronger for compounds of higher molecular mass as the effect of a single atom on the overall isotopic pattern grows smaller. On the other hand, hand-selected restrictions on this set of elements may prevent the identification of the correct molecular formula. Thus, it is a crucial step to determine the set of elements most likely comprising the compound prior to the assignment of an elemental formula to an exact mass. In this paper, we present a method to determine the presence of certain elements (sulfur, chlorine, bromine, boron, and selenium) in the compound from its (high mass accuracy) isotopic pattern. We limit ourselves to biomolecules, in the sense of products from nature or synthetic products with potential bioactivity. The classifiers developed here predict the presence of an element with a very high sensitivity and high specificity. We evaluate classifiers on three real-world data sets with 663 isotope patterns in total: 184 isotope patterns containing sulfur, 187 containing chlorine, 14 containing bromine, one containing boron, one containing selenium. In no case do we make a false negative prediction; for chlorine, bromine, boron, and selenium, we make ten false positive predictions in total. We also demonstrate the impact of our method on the identification of molecular formulas, in particular on the number of considered candidates and running time. The element prediction will be part of the next SIRIUS release, available from https://bio.informatik.uni-jena.de/software/sirius/.
Unlocking the biochemical stores of fungi is key for developing future pharmaceuticals. Through reduced expression of a critical histone deacetylase in Aspergillus nidulans, increases of up to 100-fold were observed in the levels of 15 new aspercryptins, recently described lipopeptides with two noncanonical amino acids derived from octanoic and dodecanoic acids. In addition to two NMR-verified structures, MS/MS networking helped uncover an additional 13 aspercryptins. The aspercryptins break the conventional structural orientation of lipopeptides and appear “backward” when compared to known compounds of this class. We have also confirmed the 14-gene aspercryptin biosynthetic gene cluster, which encodes two fatty acid synthases and several enzymes to convert saturated octanoic and dodecanoic acid to α-amino acids.
Myxobacteria are a rich source for structurally diverse secondary metabolites with intriguing biological activities. Here we report on new natural products that were isolated from myxobacteria in the period of 2011 to July 2016. Some examples of recent advances on modes-of-action are also summarised along with a more detailed overview on five compound classes currently assessed in preclinical studies.
Over the past few years, as the use of mass spectrometry (MS) has increased, multiple spectral libraries, databases and software frameworks have been created to enable sharing and searching of MS data. However, finding all the spectra that correspond to a specific compound across different databases continues to…
The cars we drive, the homes we live in, the restaurants we visit, and the laboratories and offices we work in are all a part of the modern human habitat. Remarkably, little is known about the diversity of chemicals present in these environments and to what degree molecules from our bodies influence the built environment that surrounds us and vice versa. We therefore set out to visualize the chemical diversity of five built human habitats together with their occupants, to provide a snapshot of the various molecules to which humans are exposed on a daily basis. The molecular inventory was obtained through untargeted liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis of samples from each human habitat and from the people that occupy those habitats. Mapping MS-derived data onto 3D models of the environments showed that frequently touched surfaces, such as handles (e.g., door, bicycle), resemble the molecular fingerprint of the human skin more closely than other surfaces that are less frequently in direct contact with humans (e.g., wall, bicycle frame). Approximately 50% of the MS/MS spectra detected were shared between people and the environment. Personal care products, plasticizers, cleaning supplies, food, food additives, and even medications that were found to be a part of the human habitat. The annotations indicate that significant transfer of chemicals takes place between us and our built environment. The workflows applied here will lay the foundation for future studies of molecular distributions in medical, forensic, architectural, space exploration, and environmental applications.
Zoanthus kuroshio is a colorful zoanthid with a fluorescent pink oral disc and brown tentacles, which dominates certain parts of the Taiwanese and Japanese coasts. This sea anemone is a rich source of biologically active alkaloids. In the current investigation, two novel halogenated zoanthamines [5α-iodozoanthenamine (1) and 11β-chloro-11-deoxykuroshine A (2)], along with four new zoanthamines [18-epi-kuroshine A (3), 7α-hydroxykuroshine E (4), 5α-methoxykuroshine E (5), and 18-epi-kuroshine E (6)], and six known compounds were isolated from Z. kuroshio. Compounds 1 and 2 are the first examples of halogenated zoanthamine-type alkaloids isolated from nature. Compounds 3 and 6 are the first zoanthamine stereoisomers with a cis-junction of the A/B rings. All isolated compounds were evaluated for their anti-inflammatory activities by measuring their effects on superoxide anion generation and elastase release by human neutrophils in response to fMLP.
The development of new antimalarial compounds remains a pivotal part of the strategy for malaria elimination. Recent large-scale phenotypic screens have provided a wealth of potential starting points for hit-to-lead campaigns. One such public set is explored, employing an open source research mechanism in which all data and ideas were shared in real time, anyone was able to participate, and patents were not sought. One chemical subseries was found to exhibit oral activity but contained a labile ester that could not be replaced without loss of activity, and the original hit exhibited remarkable sensitivity to minor structural change. A second subseries displayed high potency, including activity within gametocyte and liver stage assays, but at the cost of low solubility. As an open source research project, unexplored avenues are clearly identified and may be explored further by the community; new findings may be cumulatively added to the present work.
A dichloromethane-soluble fraction of the stem bark of Conchocarpus fontanesianus showed antifungal activity against Candida albicans in a bioautography assay. Off-line high-pressure liquid chromatography activity-based profiling of this extract enabled a precise localization of the compounds responsible for the antifungal activity that were isolated and identified as the known compounds flindersine (17) and 8-methoxyflindersine (18). As well as the identification of the bioactive principles, the ultra-high-pressure liquid chromatography–high-resolution mass spectrometry metabolite profiling of the dichloromethane stem bark fraction allowed the detection of more than 1000 components. Some of these could be assigned putatively to secondary metabolites previously isolated from the family Rutaceae. Generation of a molecular network based on MS2 spectra indicated the presence of indolopyridoquinazoline alkaloids and related scaffolds. Efficient targeted isolation of these compounds was performed by geometric transfer of the analytical high-pressure liquid chromatography profiling conditions to preparative medium-pressure liquid chromatography. This yielded six new indolopyridoquinazoline alkaloids (5, 16, 19–22) that were assigned structurally. The medium-pressure liquid chromatography separations afforded additionally 16 other compounds. This work has demonstrated the usefulness of molecular networks to target the isolation of new natural products and the value of this approach for dereplication. A detailed analysis of the constituents of the stem bark of C. fontanesianus was conducted.
Recent advances and the current status of challenging light-harvesting nanomaterials, such as semiconducting quantum dots (QDs), metal nanoparticles, semiconductor–metal heterostructures, π-conjugated semiconductor nanoparticles, organic–inorganic heterostructures, and porphyrin-based nanostructures, have been highlighted in this review. The significance of size-, shape-, and composition-dependent exciton decay dynamics and photoinduced energy transfer of QDs is addressed. A fundamental knowledge of these photophysical processes is crucial for the development of efficient light-harvesting systems, like photocatalytic and photovoltaic ones. Again, we have pointed out the impact of the metal-nanoparticle-based surface energy transfer process for developing light-harvesting systems. On the other hand, metal–semiconductor hybrid nanostructures are found to be very promising for photonic applications due to their exciton–plasmon interactions. Potential light-harvesting systems based on dye-doped π-conjugated semiconductor polymer nanoparticles and self-assembled structures of π-conjugated polymer are highlighted. We also discuss the significance of porphyrin-based nanostructures for potential light-harvesting systems. Finally, the future perspective of this research field is given.
Genome mining of the fungus Mucor irregularis (formerly known as Rhizomucor variabilis) revealed the presence of various gene clusters for secondary metabolite biosynthesis, including several terpene-based clusters. Investigation into the chemical diversity of M. irregularis QEN-189, an endophytic fungus isolated from the fresh inner tissue of the marine mangrove plant Rhizophora stylosa, resulted in the discovery of 20 structurally diverse indole-diterpenes including six new compounds, namely, rhizovarins A–F (1–6). Among them, compounds 1–3 represent the most complex members of the reported indole-diterpenes. The presence of an unusual acetal linked to a hemiketal (1) or a ketal (2 and 3) in an unprecedented 4,6,6,8,5,6,6,6,6-fused indole-diterpene ring system makes them chemically unique. Their structures and absolute configurations were elucidated by spectroscopic analysis, modified Mosher’s method, and chemical calculations. Each of the isolated compounds was evaluated for antitumor activity against HL-60 and A-549 cell lines.
Four bicyclic and three pentacyclic guanidine alkaloids (1–7) were isolated from a French Polynesian Monanchora n. sp. sponge, along with the known alkaloids monalidine A (8), enantiomers 9–11 of known natural product crambescins, and the known crambescidins 12–15. Structures were assigned by spectroscopic data interpretation. The relative and absolute configurations of the alkaloids were established by analysis of 1H NMR and NOESY spectra and by circular dichroism analysis. The new norcrambescidic acid (7) corresponds to interesting biosynthetic variation within the pentacyclic core. All compounds exhibited antiproliferative and cytotoxic efficacy against KB, HCT116, HL60, MRC5, and B16F10 cancer cells, with IC50 values ranging from 4 nM to 10 μM.
Metabolomics, the analysis of potentially all small molecules within a biological system, has become a valuable tool for biomarker identification and the elucidation of biological processes. While metabolites are often present in complex mixtures at extremely different concentrations, the dynamic range of available analytical methods to capture this variance is generally limited. Here, we show that gas chromatography coupled to atmospheric pressure chemical ionization mass spectrometry (GC-APCI-MS), a state of the art analytical technology applied in metabolomics analyses, shows an average linear range (LR) of 2.39 orders of magnitude for a set of 62 metabolites from a representative compound mixture. We further developed a computational tool to extend this dynamic range on average by more than 1 order of magnitude, demonstrated with a dilution series of the compound mixture, using robust and automatic reconstruction of intensity values exceeding the detection limit. The tool is freely available as an R package (CorrectOverloadedPeaks) from CRAN (https://cran.r-project.org/) and can be incorporated in a metabolomics data processing pipeline facilitating large screening assays.
Bottromycin A2 is a structurally unique ribosomally synthesized and post-translationally modified peptide (RiPP) that possesses potent antibacterial activity towards multidrug-resistant bacteria. The structural novelty of bottromycin stems from its unprecedented macrocyclic amidine and rare β-methylated amino acid residues. The N-terminus of a precursor peptide (BtmD) is converted into bottromycin A2 by tailoring enzymes encoded in the btm gene cluster. However, little was known about key transformations in this pathway, including the unprecedented macrocyclization. To understand the pathway in detail, an untargeted metabolomic approach that harnesses mass spectral networking was used to assess the metabolomes of a series of pathway mutants. This analysis has yielded key information on the function of a variety of previously uncharacterized biosynthetic enzymes, including a YcaO domain protein and a partner protein that together catalyze the macrocyclization.
William J. K. Crone, Natalia M. Vior, Javier Santos-Aberturas, Lukas G. Schmitz, Finian J. Leeper, and Andrew W. Truman*
Angewandte Chemistry International Edition: DOI: 10.1002/anie.201604304
Application of molecular networks for biosynthetics pathways elucidation
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