Reconstruction of HMBC Correlation Networks: A Novel NMR-Based Contribution to Metabolite Mixture Analysis.

A new in silico method is introduced for the dereplication of natural metabolite mixtures based on HMBC and HSQC spectra that inform about short-range and long-range H-C correlations occurring in the carbon skeleton of individual chemical entities. Starting from the HMBC spectrum of a metabolite mixture, an algorithm was developed in order to recover individualized HMBC footprints of the mixture constituents. The collected H-C correlations are represented by a network of NMR peaks connected to each other when sharing either a 1H or 13C chemical shift value. The network obtained is then divided into clusters using a community detection algorithm, and finally each cluster is tentatively assigned to a molecular structure by means of a NMR chemical shift database containing the theoretical HMBC and HSQC correlation data of a range of natural metabolites. The proof of principle of this method is demonstrated on a model mixture of 3 known natural compounds and then on a real-life bark extract obtained from the common spruce (Picea abies L.).

Discovery of New Inhibitors of Toxoplasma gondii via the Pathogen Box.

Toxoplasma gondii is a cosmopolitan protozoan parasite which affects approximately 30% of the population worldwide. The drugs currently used against toxoplasmosis are few in number and show several limitations, such as drug intolerance, poor bioavailability, or drug resistance mechanism developed by the parasite. Thus, it is important to find new compounds able to inhibit parasite invasion or proliferation. In this study, the 400 compounds of the open-access Pathogen Box, provided by the Medicines for Malaria Venture (MMV) foundation, were screened for their anti-Toxoplasma gondii activity. A preliminary in vitro screening performed over 72 h by an enzyme-linked immunosorbent assay (ELISA) revealed 15 interesting compounds that were effective against T. gondii at 1 µM. Their cytotoxicity was estimated on Vero cells, and their 50% inhibitory concentrations (IC50) were further calculated. As a result, eight anti-Toxoplasma gondii compounds with an IC50 of less than 2 µM and a selectivity index (SI) value of greater than 4 were identified. The most active was MMV675968, showing an IC50 of 0.02 µM and a selectivity index value equal to 275. Two other compounds, MMV689480 and MMV687807, also showed a good activity against T. gondii, with IC50s of 0.10 µM (SI of 86.6) and 0.15 µM (SI of 11.3), respectively. Structure-activity relationships for the eight selected compounds also were discussed on the basis of fingerprinting similarity measurements using the Tanimoto method. The anti-Toxoplasma gondii compounds highlighted here represent potential candidates for the development of new drugs that could be used against toxoplasmosis.

Computer-aided Dereplication and Structure Elucidation of Natural Products at the University of Reims.

Natural product chemistry began in Reims, France, in a pharmacognosy research laboratory whose main emphasis was the isolation and identification of bioactive molecules, following the guidelines of chemotaxonomy. The structure elucidation of new compounds of steadily increasing complexity favored the emergence of methodological work in nuclear magnetic resonance. As a result, our group was the first to report the use of proton-detected heteronuclear chemical shift correlation spectra for the computer-assisted structure elucidation of small organic molecules driven by atom proximity relationships and without relying on databases. The early detection of known compounds appeared as a necessity in order to deal more efficiently with complex plant extracts. This goal was reached by an original combination of mixture fractionation by centrifugal partition chromatography, analysis by 13 C NMR, digital data reduction and alignment, hierarchical data clustering, and computer database search.

Computer-Aided 13C NMR Chemical Profiling of Crude Natural Extracts without Fractionation.

A computer-aided, 13C NMR-based dereplication method is presented for the chemical profiling of natural extracts without any fractionation. An algorithm was developed in order to compare the 13C NMR chemical shifts obtained from a single routine spectrum with a set of predicted NMR data stored in a natural metabolite database. The algorithm evaluates the quality of the matching between experimental and predicted data by calculating a score function and returns the list of metabolites that are most likely to be present in the studied extract. The proof of principle of the method is demonstrated on a crude alkaloid extract obtained from the leaves of Peumus boldus, resulting in the identification of eight alkaloids, including isocorydine, rogersine, boldine, reticuline, coclaurine, laurotetanine, N-methylcoclaurine, and norisocorydine, as well as three monoterpenes, namely, p-cymene, eucalyptol, and α-terpinene. The results were compared to those obtained with other methods, either involving a fractionation step before the chemical profiling process or using mass spectrometry detection in the infusion mode or coupled to gas chromatography.

In Vitro Dermo-Cosmetic Evaluation of Bark Extracts from Common Temperate Trees.

Wood residues produced from forestry activities represent an interesting source of biologically active, high value-added secondary metabolites. In this study, 30 extracts from 10 barks of deciduous and coniferous tree species were investigated for their potential dermo-cosmetic use. The extracts were obtained from Fagus sylvatica, Quercus robur, Alnus glutinosa, Prunus avium, Acer pseudoplatanus, Fraxinus excelsior, Populus robusta, Larix decidua, Picea abies, and Populus tremula after three successive solid/liquid extractions of the barks with n-heptane, methanol, and methanol/water. All extracts were evaluated for their radical scavenging capacity, for their elastase, collagenase, and tyrosinase inhibitory activities, as well as for their antibacterial activity against gram-positive Staphylococcus aureus. In parallel, the global metabolite profiles of all extracts were established by 1D and 2D NMR and related to their biological activity. The results showed that the methanol extracts of Q. robur, A. glutinosa, L. decidua, and P. abies barks exhibit particularly high activities on most bioassays, suggesting their promising use as active ingredients in the dermo-cosmetic industry.