Dataset Information

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

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

SUBMITTER: Gaudencio SP

PROVIDER: S-EPMC10222211 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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Publications

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

Gaudêncio Susana P SP Bayram Engin E Lukić Bilela Lada L Cueto Mercedes M Díaz-Marrero Ana R AR Haznedaroglu Berat Z BZ Jimenez Carlos C Mandalakis Manolis M Pereira Florbela F Reyes Fernando F Tasdemir Deniz D

Marine drugs 20230519 5

Natural Products (NP) are essential for the discovery of novel drugs and products for numerous biotechnological applications. The NP discovery process is expensive and time-consuming, having as major hurdles dereplication (early identification of known compounds) and structure elucidation, particularly the determination of the absolute configuration of metabolites with stereogenic centers. This review comprehensively focuses on recent technological and instrumental advances, highlighting the dev ...[more]

PMID: 37233502

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Project description:Plant extracts are a potential source of new compounds for nematode control and may be an excellent alternative for the control gastrointestinal nematodes that are resistant to conventional anthelmintics. However, research involving natural products is a complex process. The main challenge is the identification of bioactive compounds. Online analytical techniques with universal detectors, such as high-performance liquid chromatography-mass spectrometry (HPLC-MS), together with metabolomics could enable the fast, accurate evaluation of a massive amount of data, constituting a viable option for the identification of active compounds in plant extracts. This study focused on the evaluation of the ovicidal activity of ethanol extracts from 17 plants collected from the Pantanal wetland in the state of Mato Grosso do Sul, Brazil, against eggs of Haemonchus placei using the egg hatchability test. The ethanol extracts were obtained using accelerated solvent extraction. The data on ovicidal activity, mass spectrometry and metabolomics were evaluated using HPLC-DAD-MS, partial least squares regression analysis (PLS-DA) and a correlation map (univariate correlation analyses) to detect compounds that have a positive correlation with biological activity. Among the ten metabolites with the best correlation coefficients, six were phenylpropanoids, two were triterpene saponins, one was a brevipolide, and one was a flavonoid. Combinations of metabolites with high ovicidal action were also identified, such as phenylpropanoids combined with the triterpene saponins and the flavonoid, flavonoids combined with iridoid and phenylpropanoids, and saponins combined with phenylpropanoid. The positive correlation between classes of compounds in plants belonging to different genera and biological activity (as previously identified in the literature) reinforces the robustness of the statistical data and demonstrates the efficacy of this method for the selection of bioactive compounds without the need for isolation and reevaluation. The proposed method also enables the determination of synergism among the classes, which would be impracticable using traditional methods. The present investigation demonstrates that the metabolomic technique was efficient at detecting secondary metabolites with ovicidal activity against H. placei. Thus, the use of metabolomics can be a tool to accelerate and simplify bioprospecting research with plant extracts in veterinary parasitology.

Project description:Diffusion-ordered NMR spectroscopy (DOSY) can be used to analyze mixtures of compounds since resonances deriving from different compounds are distinguished by their diffusion coefficients (D). Previously, DOSY has mostly been used for organometallic and polymer analysis, we have now applied DOSY to investigate diffusion coefficients of structurally diverse organic compounds such as natural products (NP). The experimental Ds derived from 55 diverse NPs has allowed us to establish a power law relationship between D and molecular weight (MW) and therefore predict MW from experimental D. We have shown that D is also affected by factors such as hydrogen bonding, molar density and molecular shape of the compound and we have generated new models that incorporate experimentally derived variables for these factors so that more accurate predictions of MW can be calculated from experimental D. The recognition that multiple physicochemical properties affect D has allowed us to generate a polynomial equation based on multiple linear regression analysis of eight calculated physicochemical properties from 63 compounds to accurately correlate predicted D with experimental D for any known organic compound. This equation has been used to calculate predicted D for 217 043 compounds present in a publicly available natural product database (DEREP-NP) and to dereplicate known NPs in a mixture based on matching of experimental D and structural features derived from NMR analysis with predicted D and calculated structural features in the database. These models have been validated by the dereplication of a mixture of two known sesquiterpenes obtained from Tasmannia xerophila and the identification of new alkaloids from the bryozoan Amathia lamourouxi. These new methodologies allow the MW of compounds in mixtures to be predicted without the need for MS analysis, the dereplication of known compounds and identification of new compounds based solely on parameters derived by DOSY NMR.

Dataset Information

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

Publications

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

Similar Datasets

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