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In Silico Studies Designed to Select Sesquiterpene Lactones with Potential Antichagasic Activity from an In‐House Asteraceae Database
ChemMedChem ( IF 3.4 ) Pub Date : 2018-02-06 , DOI: 10.1002/cmdc.201700743
Chonny Herrera Acevedo 1 , Luciana Scotti 1 , Marcus Tullius Scotti 1
Affiliation  

Chagas disease is an endemic disease caused by Trypanosoma cruzi, which affects more than eight million people, mostly in the Americas. A search for new treatments is necessary to control and eliminate this disease. Sesquiterpene lactones (SLs) are an interesting group of secondary metabolites characteristic of the Asteraceae family that have presented a wide range of biological activities. From the ChEMBL database, we selected a diverse set of 4452, 1635, and 1322 structures with tested activity against the three T. cruzi parasitic forms: amastigote, trypomastigote, and epimastigote, respectively, to create random forest (RF) models with an accuracy of greater than 74 % for cross‐validation and test sets. Afterward, a ligand‐based virtual screen of the entire SLs of the Asteraceae database stored in SistematX (1306 structures) was performed. In addition, a structure‐based virtual screen was also performed for the same set of SLs using molecular docking. Finally, using an approach combining ligand‐based and structure‐based virtual screening along with the equations proposed in this study to normalize the probability scores, we verified potentially active compounds and established a possible mechanism of action.

中文翻译:

在计算机模拟研究中,旨在从室内菊科数据库中选择具有潜在抗chachagasic活性的倍半萜烯内酯

恰加斯病是一种由克氏锥虫引起的地方性疾病,它影响了800万以上的人,其中大多数在美洲。寻找新的治疗方法对于控制和消除这种疾病是必要的。倍半萜内酯(SLs)是菊科家族的一个有趣的次级代谢产物,具有广泛的生物活性。从ChEMBL数据库中,我们选择了一组不同的4452、1635和1322结构,这些结构具有针对三种曲霉的测试活性寄生形式:鞭毛体,锥鞭毛体和附鞭毛体,分别创建随机森林(RF)模型,其交叉验证和测试集的准确性大于74%。之后,对存储在SistematX(1306种结构)中的菊科数据库的整个SL进行基于配体的虚拟筛选。此外,还使用分子对接对同一套SL进行了基于结构的虚拟屏幕。最后,使用结合基于配体和基于结构的虚拟筛选以及本研究中提出的方程式对概率得分进行归一化的方法,我们验证了潜在的活性化合物并建立了可能的作用机理。
更新日期:2018-02-06
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