通过附着-拉伸-释放分子动力学模拟研究,预测CB7与类化合物的结合亲和力和度
Xiru Wu1, Lingzhi Wang1, Yuan Qin1
1Guangxi Key Laboratory of Marine Drugs/Institute of Marine Drugs, Guangxi University of Chinese Medicine, Nanning, 530200, PR China.
Journal of molecular graphics & modelling
|June 9, 2024
概括
附着-拉开-释放 (APR) 方法准确地预测了宿主-客人结合亲和力. 将GAFF2力场与SPC/E水模型相结合,为库库比特[7]uril和类化合物复合物产生了最好的结果.
科学领域:
- 计算化学的计算化学
- 分子建模分子建模
- 超分子化学 超分子化学
背景情况:
- 宿主-客人复杂化对于分子设计至关重要.
- 准确预测结合亲和力和度是必不可少的.
- 附加拉释 (APR) 方法对结合亲和力预测有希望.
研究的目的:
- 评估APR方法的实际性能.
- 评估主机-客户系统的不同力场和水模型组合.
- 为了研究黄素[7]uril (CB7) 与四种类化合物的结合亲和力.
主要方法:
- 计算使用附加-拉伸-释放 (APR) 方法进行.
- 测试了两个力场 (GAFF,GAFF2) 和三个水模型 (TIP3P,SPC/E,OPC).
- 这项研究的重点是黄[7]uril (CB7) 复合与柏柏林,科普蒂辛,柏林和棕.
主要成果:
- GAFF2力场和SPC/E水模型的组合显示出最佳性能 (R2=0.95,RMSD=3.04 kcal/mol).
- GAFF力场始终高估了结合亲和力,表明了潜在的系统错误.
- 预测准确度对所使用的特定力场和水模型组合敏感.
结论:
- GAFF2/SPC/E组合提供了一个可靠的方法来预测CB7-类系统中的结合亲和关系.
- 精心选择力场和水模型对于准确的计算预测至关重要.
- 建议使用多种力场组合进行进一步的模拟,以进行可靠的分析.
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