测试激进剂DPI-287对三角片受体和新型激进剂的激活机制,使用基于组合的虚拟查与分子动力学模拟
Emily Dean1, AnneMarie Dominique1, Americus Palillero1
1Department of Molecular & Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States.
通过分子动力学和虚拟查,确定了新的三角形阿片类受体 (DOR) 激活剂. 这些新型化合物显示出对非成性疼痛缓解的承诺,对DOR比其他阿片类受体具有高选择性.
科学领域:
- 药理学 药理学是指药理学的学科.
- 计算化学的计算化学
- 神经科学是一个神经科学.
背景情况:
- 穆阿片类受体激动剂会导致成,导致人们需要更安全的止痛药.
- 德尔塔阿片类受体 (DOR) 激动剂提供了一个潜在的非成的替代品.
- 没有FDA批准的DOR激动剂存在,为药物发现创造了机会.
研究的目的:
- 通过基于结构的虚拟查来识别新的DOR激动剂.
- 探索DOR的形状动态,以改善查.
- 评估潜在的DOR激动剂的选择性和激活机制.
主要方法:
- 分子动力学 (MD) 模拟以探测DOR形态可塑性.
- 聚类分析以确定具有代表性的DOR形状.
- 基于结构的虚拟选ZINC数据库与DOR对应.
- 使用MD模拟和MM-GBSA进行具有约束力的稳定性评估.
- 动态网络分析以研究受体-连接体通信.
- 对卡帕和片受体进行对接研究,用于选择性分析.
主要成果:
- 从MD模拟中确定了两个代表性的DOR构造.
- 选了1700万种化合物,选择了69种潜在的激动剂.
- 在前69个化合物中,有37个由模拟形状识别出来.
- 根据结合能量和特性选择了八种最有利的化合物.
- 在八个有利的化合物中,有六个来自模拟形状.
- 分析证实了与已知的激动剂共享的激活机制.
- 对接研究表明DOR对卡帕和Mu受体具有良好的选择性.
结论:
- MD模拟通过捕捉DOR形态动态来增强虚拟选.
- 确定了有前途的新型DOR激动剂,具有非成性疼痛管理的潜力.
- 已识别的化合物对DOR具有很高的选择性,最大限度地减少了非目标效应.
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