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Selection of antileishmanial sesquiterpene lactones from SistematX database using a combined ligand-/structure-based virtual screening approach

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Abstract

Leishmaniasis refers to a complex of diseases, caused by the intracellular parasitic protozoans belonging to the genus Leishmania. Among the three types of disease manifestations, the most severe type is visceral leishmaniasis, which is caused by Leishmania donovani, and is diagnosed in more than 20,000 cases annually, worldwide. Because the current therapeutic options for disease treatment are associated with several limitations, the identification of new potential leads/drugs remains necessary. In this study, a combined approach was used, based on two different virtual screening (VS) methods, which were designed to select promising antileishmanial agents from among the entire sesquiterpene lactone (SL) dataset registered in SistematX, a web interface for managing a secondary metabolite database that is accessible by multiple platforms on the Internet. Thus, a ChEMBL dataset, including 3159 and 1569 structures that were previously tested against L. donovani amastigotes and promastigotes in vitro, respectively, was used to develop two random forest models, which performed with greater than 74% accuracy in both the cross-validation and test sets. Subsequently, a ligand-based VS assay was performed against the 1306 SistematX-registered SLs. In parallel, the crystal structures of three L. donovani target proteins, N-myristoyltransferase, ornithine decarboxylase, and mitogen-activated protein kinase 3, and a homology model of pteridine reductase 1 were used to perform a structure-based VS, using molecular docking, of the entire SistematX SL dataset. The consensus analysis of these two VS approaches resulted in the normalization of probability scores and identified 13 promising, enzyme-targeting, antileishmanial SLs from SistematX that may act against L. donovani.

Graphic abstract

A combined approach based on two different virtual screening methods (structure-based and ligand-based) was performed using an in-house dataset composed of 1306 sesquiterpene lactones to identify potential antileishmanial (Leishmania donovani) structures.

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Acknowledgements

We thank the CNPq and Capes for financial Support, Grant Numbers 309648/2019-0 and 431254/2018-4, and the Student Agreement Program of Graduate—PEC-PG of CNPq—Brazil. UMNG is also thanked for the financial support through Project IMP-CIAS-2924. This study was performed as part of the activities of the Research Network Natural Products against Neglected Diseases (ResNet-NPND), https://resnetnpnd.org/.

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  1. Post-Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, João Pessoa, PB, 58051-900, Brazil

    Chonny Herrera-Acevedo, Mayara Dos Santos Maia, Élida Batista Vieira Sousa Cavalcanti, Luciana Scotti & Marcus Tullius Scotti

  2. Bioorganic Chemistry Laboratory, Facultad de Ciencias Básicas y Aplicadas, Universidad Militar Nueva Granada, Cajicá, 250247, Colombia

    Chonny Herrera-Acevedo & Ericsson Coy-Barrera

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Herrera-Acevedo, C., Dos Santos Maia, M., Cavalcanti, É.B.V.S. et al. Selection of antileishmanial sesquiterpene lactones from SistematX database using a combined ligand-/structure-based virtual screening approach. Mol Divers 25, 2411–2427 (2021). https://doi.org/10.1007/s11030-020-10139-6

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