统计建模来量化FoldX预测的蛋白质折叠和结合稳定性的不确定性
Yesol Sapozhnikov1, Jagdish Suresh Patel2,3, F Marty Ytreberg4,3
1Program in Bioinformatics and Computational Biology, University of Idaho, Moscow, ID, 83844, USA.
BMC bioinformatics
|November 12, 2023
概括
我们开发了一个统计框架来量化计算蛋白质稳定性预测中的不确定性. 这种方法通过将分子动力学模拟纳入FoldX工作流来提高准确性,为蛋白质变异提供可靠的估计.
科学领域:
- 计算生物学是一种计算生物学.
- 蛋白质工程是一种蛋白质工程.
- 生物信息学是一种生物信息学.
背景情况:
- 在高通量研究中,计算方法对于预测蛋白质稳定性变化来自误解突变的变化至关重要.
- 目前的方法在准确性和评估预测不确定性方面面临挑战.
- FoldX是这些预测的广泛使用的工具.
研究的目的:
- 使用FoldX.开发一个统计框架来量化使用FoldX预测的蛋白质稳定性变化的不确定性.
- 提高蛋白质变体计算预测的可靠性.
主要方法:
- 开发了多个线性回归模型来量化预测不确定性.
- 将分子动力学 (MD) 模拟集成到 FoldX 工作流中.
- 使用FoldX能量术语,残留生物化学性质和MD可变性用于不确定性估计.
主要成果:
- 线性回归模型有效量化了FoldX预测中对个别突变的不确定性.
- 随着MD模拟的加入,模型精度显著提高.
- 确定的不确定性的一般上限:±2.9 kcal/mol (折叠) 和±3.5 kcal/mol (结合).
结论:
- 一个简单的线性回归框架可以预测FoldX稳定性预测中的不确定性.
- 开发的技术可以适应其他计算预测方法.
- 这种方法提高了计算工具在蛋白质变体分析中的实用性.
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