| Autor: |
Barbosa H; Center for Natural and Human Sciences, Federal University of ABC, São Paulo 09210-180, Brazil., Espinoza GZ; School of Arts, Science, and Humanities, University of São Paulo, São Paulo 03828-000, Brazil., Amaral M; Laboratory of Pathophysiology, Butantan Institute, São Paulo 05503-900, Brazil., de Castro Levatti EV; Laboratory of Pathophysiology, Butantan Institute, São Paulo 05503-900, Brazil., Abiuzi MB; Laboratory of Pathophysiology, Butantan Institute, São Paulo 05503-900, Brazil., Veríssimo GC; Department of Pharmaceutical Products, Federal University of Minas Gerais, Minas Gerais, 31270-901, Brazil., Fernandes PO; Department of Pharmaceutical Products, Federal University of Minas Gerais, Minas Gerais, 31270-901, Brazil., Maltarollo VG; Department of Pharmaceutical Products, Federal University of Minas Gerais, Minas Gerais, 31270-901, Brazil., Tempone AG; Laboratory of Pathophysiology, Butantan Institute, São Paulo 05503-900, Brazil., Honorio KM; Center for Natural and Human Sciences, Federal University of ABC, São Paulo 09210-180, Brazil.; School of Arts, Science, and Humanities, University of São Paulo, São Paulo 03828-000, Brazil., Lago JHG; Center for Natural and Human Sciences, Federal University of ABC, São Paulo 09210-180, Brazil. |
| Abstrakt: |
American Trypanosomiasis, also known as Chagas disease, is caused by the protozoan Trypanosoma cruzi and exhibits limited options for treatment. Natural products offer various structurally complex metabolites with biological activities, including those with anti- T. cruzi potential. The discovery and development of prototypes based on natural products frequently display multiple phases that could be facilitated by machine learning techniques to provide a fast and efficient method for selecting new hit candidates. Using Random Forest and k-Nearest Neighbors, two models were constructed to predict the biological activity of natural products from plants against intracellular amastigotes of T. cruzi . The diterpenoid andrographolide was identified from a virtual screening as a promising hit compound. Hereafter, it was isolated from Cymbopogon schoenanthus and chemically characterized by spectral data analysis. Andrographolide was evaluated against trypomastigote and amastigote forms of T. cruzi , showing IC 50 values of 29.4 and 2.9 μM, respectively, while the standard drug benznidazole displayed IC 50 values of 17.7 and 5.0 μM, respectively. Additionally, the isolated compound exhibited a reduced cytotoxicity (CC 50 = 92.8 μM) against mammalian cells and afforded a selectivity index (SI) of 32, similar to that of benznidazole (SI = 39). From the in silico analyses, we can conclude that andrographolide fulfills many requirements implemented by DND i to be a hit compound. Therefore, this work successfully obtained machine learning models capable of predicting the activity of compounds against intracellular forms of T. cruzi . |
