Improved Sampling Strategies for Protein Model Refinement Based on Molecular Dynamics Simulation.
Improved Sampling Strategies for Protein Model Refinement Based on Molecular Dynamics Simulation.
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DOI：
10.1021/acs.jctc.0c01238
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发表时间：
2021-03-09
影响因子：
5.5
通讯作者：
Feig M
中科院分区：
文献类型：
--
作者：
Heo L;Arbour CF;Janson G;Feig M
蛋白质结构为理解生物过程提供了有价值的信息。蛋白质结构可以通过实验方法确定，如X射线晶体学，核磁共振（NMR）光谱学或低温电子显微镜。作为替代，计算机模拟方法可用于预测蛋白质结构。这些方法利用蛋白质结构数据库通过基于模板的建模进行结构预测或用于训练机器学习模型以生成预测。对于远离已知结构的蛋白质的结构预测通常导致相对于真实生理结构的较低准确度。基于物理的蛋白质模型精化方法可以应用于提高预测模型中的模型精度。细化方法依赖于预测结构周围的构象采样，如果更接近天然状态的结构被采样，则模型质量的改进成为可能。分子动力学模拟已经特别成功地提高模型的质量，但尽管可以实现一致的细化，模型质量的改善仍然是温和的。为了扩展基于模拟的协议的细化性能，我们探索了新的方案，重点是优化偏置函数的使用和增加模拟温度的应用。此外，我们测试了使用替代的初始模型，使模拟可以更广泛地探索构象空间。基于这种分析的见解，我们提出了一种新的改进协议，显着优于以前的国家的最先进的分子动力学模拟为基础的协议在这里描述的基准测试。
Protein structures provide valuable information for understanding biological processes. Protein structures can be determined by experimental methods such as X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, or cryogenic electron microscopy. As an alternative, in silico methods can be used to predict protein structures. Those methods utilize protein structure databases for structure prediction via template-based modeling or for training machine-learning models to generate predictions. Structure prediction for proteins distant from proteins with known structures often results in lower accuracy with respect to the true physiological structures. Physics-based protein model refinement methods can be applied to improve model accuracy in the predicted models. Refinement methods rely on conformational sampling around the predicted structures, and if structures closer to the native states are sampled, improvements in the model quality become possible. Molecular dynamics simulations have been especially successful for improving model qualities but although consistent refinement can be achieved, the improvements in model qualities are still moderate. To extend the refinement performance of a simulation-based protocol, we explored new schemes that focus on an optimized use of biasing functions and the application of increased simulation temperatures. In addition, we tested the use of alternative initial models so that the simulations can explore conformational space more broadly. Based on the insight of this analysis we are proposing a new refinement protocol that significantly outperformed previous state-of-the-art molecular dynamics simulation-based protocols in the benchmark tests described here.
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影响因子：
2.9
作者：
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通讯作者：
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影响因子：
4.4
作者：
JORGENSEN, WL;CHANDRASEKHAR, J;KLEIN, ML
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KLEIN, ML
影响因子：
2.9
作者：
Heo, Lim;Arbour, Collin F.;Feig, Michael
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Feig, Michael
影响因子：
4.3
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通讯作者：
Pande VS
影响因子：
2.9
作者：
Heo, Lim;Feig, Michael
通讯作者：
Feig, Michael