Selection of antileishmanial sesquiterpene lactones from SistematX database using a combined ligand-/structure-based vir
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ORIGINAL ARTICLE
Selection of antileishmanial sesquiterpene lactones from SistematX database using a combined ligand‑/structure‑based virtual screening approach Chonny Herrera‑Acevedo1,2 · Mayara Dos Santos Maia1 · Élida Batista Vieira Sousa Cavalcanti1 · Ericsson Coy‑Barrera2 · Luciana Scotti1 · Marcus Tullius Scotti1 Received: 7 July 2020 / Accepted: 30 August 2020 © Springer Nature Switzerland AG 2020
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.
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11030-020-10139-6) contains supplementary material, which is available to authorized users. * Marcus Tullius Scotti [email protected] 1
Post‑Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, João Pessoa, PB 58051‑900, Brazil
Bioorganic Chemistry Laboratory, Facultad de Ciencias Básicas y Aplicadas, Universidad Militar Nueva Granada, Cajicá 250247, Colombia
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Molecular Diversity
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.
Keywords Leishma
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