安德罗格拉福利德:来自Cymbopogon schoenanthus的Diterpenoid被确定为一种新的打击Trypanosoma cruzi的化合物,使用机器学习和实验方法
Henrique Barbosa1, Gabriel Zarzana Espinoza2, Maiara Amaral3
1Center for Natural and Human Sciences, Federal University of ABC, São Paulo 09210-180, Brazil.
Journal of chemical information and modeling
|December 27, 2023
概括
机器学习模型确定了来自植物的andrographolide作为治疗查加斯病 (美国三虫病) 的有前途的天然产品. 这种化合物对寄生虫Trypanosoma cruzi具有显著的活性,对哺乳动物细胞的毒性较低.
科学领域:
- 自然产品化学 自然产品化学
- 计算化学的计算化学
- 寄生虫学的寄生虫学
背景情况:
- 查加斯病是由Trypanosoma cruzi引起的,其治疗选择有限.
- 自然产品是潜在的抗寄生虫化合物的丰富来源.
- 机器学习可以加速从自然产品中发现新的候选药物.
研究的目的:
- 开发机器学习模型,用于预测天然产品的抗Trypanosoma cruzi活性.
- 识别和验证有希望的基于天然产品的打击化合物用于查加斯病治疗.
主要方法:
- 随机森林和k-最近邻居模型被用于虚拟选.
- 安德罗格拉福利德从Cymbopogon schoenanthus中分离出来,并进行了化学表征.
- 在体外测试中评估了andrographolide与Trypanosoma cruzi形式和哺乳动物细胞.
主要成果:
- 机器学习模型成功预测了反T. cruzi活动.
- 安德罗格拉福利德对T.cruzi黄虫 (IC50 = 2.9 μM) 和三虫 (IC50 = 29.4 μM) 具有强烈的活性.
- 该化合物表现出有利的细胞毒性 (CC50 = 92.8 μM) 和选择性指数 (SI = 32),与尼达相似.
结论:
- 机器学习模型对于识别潜在的反查加斯病原体是有效的.
- 安德罗格拉福利德是一种有前途的打击化合物,用于进一步开发对抗美国 trypanosomiasis.
- 这项研究强调了天然产品和计算方法在治疗被忽视疾病的药物发现方面的潜力.
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