Deciphering the complexity of the chemicals in food packaging materials using molecular networks.

Chemicals from packaging materials might be transferred into food resulting in consumer exposure. Identifying these migrated chemicals is highly challenging and crucial to perform their safety assessment, usually starting by the understanding of the chemical composition of the packaging material itself. This study explores the use of the Molecular Networking (MN) approach to support identification of the extracted chemicals.

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 H or C chemical shift value.

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

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.

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.

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

A computer-aided, C 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 C 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.

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 , and after three successive solid/liquid extractions of the barks with heptane, methanol, and methanol/water.