使用定量结构-活动关系模型评估Cx43间隙结阻尼剂
Ramona Matusevičiūtė1, Eglė Ignatavičiūtė1, Rokas Mickus2
1Faculty of Medicine, Lithuanian University of Health Sciences, 03101 Kaunas, Lithuania.
Biomedicines
|July 29, 2023
概括
定量结构-活性关系 (QSAR) 模型精确地识别了强大的连xin-43 (Cx43) 间隙结 (GJ) 抑制剂,用于心脏病. 与分子对接相比,QSAR模型与实验数据的相关性较好,用于预测抑制剂疗效.
科学领域:
- 心血管药理学心血管药理学
- 分子生物学分子生物学
- 计算化学的计算化学
背景情况:
- 连接素-43 (Cx43) 间隙连接 (GJ) 对于心脏电脉冲传导至关重要.
- 调节Cx43 GJ活动为心律失常提供了治疗潜力.
- 分子对接对GJ抑制剂强度的预测准确性有限.
研究的目的:
- 证明定量结构-活性关系 (QSAR) 模型用于识别强大的Cx43 GJ抑制剂的实用性.
- 为了比较QSAR和Cx43 GJ抑制剂的分子对接的预测性能.
主要方法:
- 通过分子对接,QSAR和3D-QSAR评估了16种已知的Cx43 GJ抑制剂.
- 建议并经过实验测试的d-limonene作为HeLa细胞中的假定Cx43抑制剂.
- 将预测的抑制度 (pIC50) 与实验值 (eIC50) 进行比较.
主要成果:
- QSAR和3D-QSAR模型显示,预测和实验功率之间存在强烈的相关性 (R=0.88,R=0.90).
- 分子对接显示,与实验功率的相关性较弱 (R=0.78).
- 鉴定出d-limonene是一种假定的Cx43 GJ抑制剂.
结论:
- QSAR建模提供了一个比单独的分子对接更精确的方法来识别强大的Cx43 GJ抑制剂.
- 该研究建议QSAR用于新型GJ通道抑制剂的初级查,随后进行补丁验证.
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