Jamroz Michal, Kolinski Andrzej, Kmiecik Sebastian
Laboratory of Theory of Biopolymers, Faculty of Chemistry, University of Warsaw, Warsaw, Poland.
Methods Mol Biol. 2014;1137:235-50. doi: 10.1007/978-1-4939-0366-5_16.
Coarse-grained (CG) modeling is a well-acknowledged simulation approach for getting insight into long-time scale protein folding events at reasonable computational cost. Depending on the design of a CG model, the simulation protocols vary from highly case-specific-requiring user-defined assumptions about the folding scenario-to more sophisticated blind prediction methods for which only a protein sequence is required. Here we describe the framework protocol for the simulations of long-term dynamics of globular proteins, with the use of the CABS CG protein model and sequence data. The simulations can start from a random or a selected (e.g., native) structure. The described protocol has been validated using experimental data for protein folding model systems-the prediction results agreed well with the experimental results.
粗粒度(CG)建模是一种公认的模拟方法,能够以合理的计算成本深入了解长时间尺度的蛋白质折叠事件。根据CG模型的设计,模拟协议各不相同,从高度依赖特定情况(需要用户对折叠场景进行自定义假设)到更复杂的盲预测方法(仅需要蛋白质序列)。在这里,我们描述了使用CABS CG蛋白质模型和序列数据模拟球状蛋白质长期动力学的框架协议。模拟可以从随机结构或选定结构(例如天然结构)开始。所描述的协议已通过蛋白质折叠模型系统的实验数据进行了验证——预测结果与实验结果吻合良好。