Andrographolide: A Diterpenoid from Cymbopogon schoenanthus Identified as a New Hit Compound against Trypanosoma cruzi Using Machine Learning and Experimental Approaches

苯硝唑 穿心莲内酯 克鲁兹锥虫 无鞭毛体 萜类 恰加斯病 生物 杀锥虫剂 生物信息学 传统医学 计算生物学 药理学 利什曼原虫 生物化学 病毒学 计算机科学 医学 寄生虫寄主 万维网 基因
作者
Henrique Barbosa,Gabriel Zarzana Espinoza,Maiara Amaral,Erica Valadares de Castro Levatti,Mariana Babberg Abiuzi,Gabriel Corrêa Veríssimo,Philipe Oliveira Fernandes,Vinícius Gonçalves Maltarollo,André G. Tempone,Káthia M. Honório,João Henrique G. Lago
出处
期刊:Journal of Chemical Information and Modeling [American Chemical Society]
卷期号:64 (7): 2565-2576 被引量:4
标识
DOI:10.1021/acs.jcim.3c01410
摘要

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 IC50 values of 29.4 and 2.9 μM, respectively, while the standard drug benznidazole displayed IC50 values of 17.7 and 5.0 μM, respectively. Additionally, the isolated compound exhibited a reduced cytotoxicity (CC50 = 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 DNDi 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.
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