计算机辅助药物设计方法用于选天然产品的结构类型,以向Leishmania spp中的基酶
Haruna Luz Barazorda-Ccahuana1, Luis Daniel Goyzueta-Mamani1,2, Mayron Antonio Candia Puma1,3
1Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Catolica de Santa Maria de Arequipa, Arequipa, Peru.
F1000Research
|July 10, 2023
概括
这项研究确定了天然产品类似物作为莱什曼病的潜在候选药物. 计算机辅助药物设计揭示了像echioidinin和malvidin这样的化合物,这些化合物有效地准了寄生虫.
科学领域:
- 计算化学是一种计算化学.
- 药物发现 药物发现
- 寄生虫学的寄生虫学
背景情况:
- 莱什曼病是一种严重的疾病,死亡率高,每年约有150万例.
- 目前针对莱什曼病的治疗方法有限且无效.
- 自然产品为新药开发提供了一个有前途的来源.
研究的目的:
- 选天然产品的结构类似物,以寻找潜在的抗莱什曼病药物候选者.
- 为了识别选择性抑制*Leishmania* arginase的化合物.
- 为了利用计算机辅助药物设计 (CADD) 进行药物发现.
主要方法:
- 使用虚拟选和分子对接.
- 分子动力学模拟和MM-GBSA用于结合自由能量的估计.
- 应用自由能量扰动 (FEP) 来评估连接体-标相互作用.
主要成果:
- 四种化合物 (2H-1-二烯,3,4-二-2-2-甲基) -9CI,echioidinin和malvidin) 显示出有前途的结果.
- 埃基奥伊丁宁和马尔维丁在*莱什马尼亚*阿基纳酶活性部位内表现出显著的相互作用.
- 选择的化合物显示没有预测的毒性.
结论:
- 埃基奥伊丁宁和马尔维丁是开发抗莱什曼病药物的潜在候选者.
- 这项研究强调了CADD在识别基于天然产品的治疗方法中的实用性.
- 建议对这些化合物进行进一步的体外和体内验证.
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