Metabolomics and dereplication strategies in the discovery of natural product derived drugs

Tawfike, AF and Tawfik, N and Edrada-Ebel, R (2015) Metabolomics and dereplication strategies in the discovery of natural product derived drugs. Planta Medica, 81 (16). SL3A_02. ISSN 0032-0943 (https://doi.org/10.1055/s-0035-1565310)

[thumbnail of Tawfike_etal_PM2015_Metabolic_and_derplication_strategies_in_the_discovery_of_natural_product_derived_drugs]
Preview
 Text. Filename: Tawfike_etal_PM2015_Metabolic_and_derplication_strategies_in_the_discovery_of_natural_product_derived_drugs.pdf
Download (4MB)| Preview

Abstract

Metabolomics is the technology designed to provide general qualitative and quantitative profile of metabolites in organisms exposed to different conditions. Metabolomics is applied in many aspects of natural drug discoveries, particularly in bioactivity screening to improve dereplication and identification procedures. Fast dereplication of known compounds and identification of lead bioactive metabolites is important in the primary stages of metabolomics profiling prior to an intensive isolation work. Two levels of metabolomics were used in this study. First was metabolites fingerprinting which aimed for rapid classification of samples by comparing the metabolites patterns or fingerprints. Second was metabolites profiling and dereplication study for class of compounds related to a specific pathway in order to individually identify and quantify these metabolites. This study involved isolation of endophytic fungus Aspergillus aculeatus from Egyptian medicinal plants, Terminalia laxiflora. Identification of the strains has been achieved through molecular biological methods. Metabolomic profiling, using NMR and HR-MS were done at different stages of the growth phase for both solid and liquid culture media. Dereplication studies were accomplished by utilizing the MZmine 2.10 software with aid of the AntiBase and DNP databases. By end of the dereplication process metabolites were sorted out into three levels; level 1: identified compounds, level 2: putatively annotated compound class and level 3: completely unidentified and unclassified compounds. Multivariate data analysis was employed by using PCA in order to classify samples into groups, trends and outliers, which maximize the information, can be obtained from spectral data. OPLS-DA was used to correlate the chemical profile with tested biological activity. Metabolomics has been shown to be a powerful facilitator in the discovery of natural products, which are considered an excellent source for novel leads.

ORCID iDs

Tawfike, AF ORCID logoORCID: https://orcid.org/0000-0003-2061-3093, Tawfik, N and Edrada-Ebel, R;
CORE (COnnecting REpositories)