Toxoplasmosis is a worldwide parasitosis that is generally benign. The infestation may pose a risk to immunocompromized patients and to fetuses when pregnant women have recently seroconverted. Current treatments have numerous side effects and chemoresistance is emerging, hence the need to find new anti-Toxoplasma gondii substances. This study focuses on the antiparasitic potential of lupane-type pentacyclic triterpenes isolated from the bark of black alder (Alnus glutinosa), as well as the hypothesis of their macromolecular target by an original method of reverse docking. Among the isolated triterpenes, betulone was the most active compound with an IC50 of 2.7 ± 1.2 μM, a CC50 greater than 80 μM, and a selectivity index of over 29.6. An additional study of the anti-T. gondii potential of commercially available compounds (betulonic acid methyl ester and betulonic acid) showed the important role of the C3 ketone function and the C28 oxidation level on the lupane-type triterpene in the antiparasitic activity since their IC50 and CC50 were similar to that of betulone. Finally, the most active compounds were subjected to the AMIDE reverse docking workflow. A dataset of 87 T. gondii proteins from the Protein Data Bank was created. It identified calcium-dependent protein kinase CDPK3 as the most likely target of betulin derivatives.
Compound identification in complex mixtures by NMR and MS is best achieved through experimental databases (DB) mining. Experimental DB frequently show limitations regarding their completeness, availability or data quality, thus making predicted database of increasing common use. Querying large databases may lead to select unlikely structure candidates. Two approaches to dereplication are thus possible: filtering of a large DB before search or scoring of the results after a large scale search. The present work relies on the former approach. As far as we know, nmrshiftdb2 is the only open‐source 13NMR chemical shift predictor that can be freely operated in batch mode. CFM‐ID 4.0 is one of the best‐performing open‐source tools for ESI‐MS/MS spectra prediction. LOTUS is a freely usable and comprehensive collection of secondary metabolites. Integrating the open source database and software LOTUS, CFM‐ID, and nmrshiftdb2 in a dereplication workflow requires presently programming skills, owing to the diversity of data encoding and processing procedures. A graphical user interface that integrates seamlessly chemical structure collection, spectral data prediction and database building still does not exist, as far as we know. The present work proposes a stand–alone software tool that assists the identification of mixture components in a simple way.
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