基于SMILES的卡尔巴酸衍生物的QSAR分析,以甲基胆化酶为向
Negin Latifi1, Shahin Ahmadi2, Shahram Lotfi3
1Department of Chemistry, TeMS.C., Islamic Azad University, Tehran, Iran.
Scientific reports
|January 28, 2026
概括
碳酸衍生物通过抑制丁醇化酶 (BuChE) 显示出对阿尔茨海默病治疗的前景. 这项研究开发了定量结构-活性关系 (QSAR) 模型,以预测和优化它们的BuChE抑制活性.
科学领域:
- 药用化学 医学化学
- 计算化学计算化学
- 神经科学是一个神经科学.
背景情况:
- 丁胆酶 (BuChE) 是阿尔茨海默病 (AD) 发病的一个关键酶.
- 抑制BuChE是AD管理的一个有前途的治疗策略.
- 碳酸衍生物是抗阿尔茨海默症药物发现的宝贵支架,因为它们具有伪不可逆转的抑制作用.
研究的目的:
- 开发定量结构-活性关系 (QSAR) 模型,用于预测碳酸衍生物的BuChE抑制活性.
- 探索化学结构和BuChE抑制功效之间的关系.
- 确定增强抑制活性的关键结构特征.
主要方法:
- 从同行评审的文献中编制了205种碳酸盐衍生物的数据集.
- 在CORAL-2023软件框架中使用蒙特卡洛优化.
- 利用来自SMILES记号和抑制分子图的混合最佳描述符.
主要成果:
- 在四个随机分割和四个目标函数中开发了60个QSAR模型.
- 基于TF3的模型表现出优异的统计性能,验证R2从0.80-0.86到Q2从0.78-0.84.
- 机械解释显示,芳香,疏水和分支碎片通过与BuChE活性部位的特定相互作用来增强活性.
结论:
- 开发的QSAR模型为设计基于碳酸盐的新型BuChE抑制剂提供了宝贵的工具.
- 像芳香性和疏水性这样的结构特征对于强大的BuChE抑制至关重要.
- 这项研究有助于合理设计针对BuChE的抗阿尔茨海默症疗法.
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