蛋白质-蛋白质相互作用对联体-蛋白质结合的影响的定量表征:多链动力学扰动分析方法
1College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, 30 South Puzhu Road, Jiangbei New District, Nanjing 211816, China.
International journal of molecular sciences
|September 14, 2024
概括
蛋白与蛋白相互作用 (PPI) 显著影响药物与蛋白质结合的方式. 一种新的多链动态扰动分析 (mcDPA) 方法模拟了这些效应,改善了复杂生物系统中药物向相互作用的预测.
科学领域:
- 生物化学和分子生物学
- 药理学和药物发现
- 计算生物学 计算生物学
背景情况:
- 蛋白与蛋白相互作用 (PPI) 关键调节联体蛋白相互作用 (LPI),影响药物疗效.
- 现有的方法很难全面预测PPI如何改变LPI.
- 了解PPI-LPI相互作用对于合理的药物设计至关重要.
研究的目的:
- 量化PPI对LPI的影响.
- 开发一种用于预测蛋白质-蛋白质复合体中小分子结合的计算方法.
- 在基准数据集和FDA批准的药物上评估方法的性能.
主要方法:
- 在蛋白质-蛋白质对接研究中检查了63个配体-蛋白质复合体.
- 开发并应用了一种多链动态扰动分析 (mcDPA) 方法.
- 量化了PPI对LPI的六种典型影响,并预测了具有约束力的区域.
主要成果:
- 在mcDPA方法捕捉了PPI诱导的变化在配体结合区域的不同精度.
- 在一个基准数据集中,52%的复合物实现了>=50%的预测准确度,55%的预测准确度是>=50%.
- 应用于FDA批准的33种针对蛋白质-蛋白质复合物的药物,准确度达到60%,回忆率为57%.
结论:
- mcDPA方法有效地模拟了PPI对LPI的影响.
- 这种方法有助于预测复杂的蛋白质环境中的药物向相互作用.
- 这些发现支持设计更有效的针对蛋白质复合体的治疗方法.
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