融合QSAR模型用于预测Cruzain抑制剂
Rafael Bello Gonçalves1, Witor Ribeiro Ferraz1, Raisa Ludmila Calil1
1Department of Pharmacy, School of Pharmaceutical Sciences, University of São Paulo, Av. Prof. Lineu Prestes 580, São Paulo-SP 05508-900, Brazil.
这项研究开发了多种定量结构-活性关系 (QSAR) 模型,以确定针对克鲁扎因的新药,这是查加斯病的关键蛋白质. 最好的模型确定了有前途的候选药物,dv007和dv015,用于进一步开发.
科学领域:
- 药用化学 医学化学
- 计算化学计算化学
- 寄生虫学的寄生虫学
背景情况:
- 查加斯病是一种寄生虫感染,由*Trypanosoma cruzi*引起.
- 克鲁扎因 (Cruzain) 是来自 *T. cruzi* 的氨酸蛋白酶,是抗毒药物发现的关键治疗标.
- 克鲁扎因在寄生虫细胞入侵,复制,分化和新陈代谢中起着至关重要的作用.
研究的目的:
- 为一组61种克鲁扎因抑制剂开发和评估各种定量结构-活性关系 (QSAR) 模型.
- 识别可靠的QSAR模型,用于预测潜在抗毒性化合物的活性.
- 引导针对查加斯病的新药候选者的虚拟查工作.
主要方法:
- 开发和评估多种QSAR模型,包括2D-QSAR,3D-QSAR (CoMFA,CoMSIA) 和HQSAR.
- 分子对接用于分子对齐.
- 使用高性能QSAR模型对化化合物的虚拟选.
主要成果:
- 产生了10个主要的和114个小的QSAR模型变化,其中78个符合可接受性标准.
- CoMFA和CoMSIA模型表现出强度,硬质场显示出令人满意的趋同.
- 最好的HQSAR模型使用了2-5个原子的碎片大小的原子和连接.
- 虚拟选确定了hydrazones dv007和dv015作为具有高预测pIC50值 (7.26和7.24) 的有希望的候选者.
结论:
- 多种QSAR模型,包括具有很少描述符的2D-QSAR,为药物发现提供了可靠的结果.
- 3D-QSAR模型对于理解连接体几何和优化抗哈加斯化合物非常有价值.
- 已识别的水子dv007和dv015代表了对实验验证和进一步开发夏加斯病药物的有希望的线索.
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