虚拟筛选
利什曼原虫
计算生物学
码头
利什曼病
细胞毒性
化学
数量结构-活动关系
药物发现
生物
计算机科学
体外
生物化学
立体化学
寄生虫寄主
免疫学
万维网
作者
Rodrigo Ochoa,Elisa García,Sara M. Robledo,Wilson Cardona‐G
标识
DOI:10.1016/j.jmgm.2019.06.015
摘要
Discovery of novel or repurposed chemical treatments for leishmaniasis is a priority given the limited number of therapeutic alternatives available. One way to accelerate the finding is by implementing virtual screening methodologies using structural information, with subsequent experimental validations. Here we tested a library of 48 phenylfuranchalcones as anti-Leishmania agents that can be associated to the potential inhibition of a protein target within the parasite. For that purpose, a list of 43 protein structures from different Leishmania species was prepared to dock the virtual compound library. The protein with the best predicted scores was used as reference to select a subset of previously synthesized compounds for in vitro validation of their cytotoxicity and anti-Leishmania activity. We found a set of active compounds (EC50 < 25 μM) that were compared with the computational results using Spearman correlations. The analysis allowed us to propose the inhibition of a phosphodiesterase enzyme as the potential mechanism of action.
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