FOLDING A MINI-PROTEIN (TRPCAGE) USING WEIGHTED ENSEMBLE PATH SAMPLING

这个子项目是利用资源的许多研究子项目之一。 由NIH/NCRR资助的中心拨款提供。对子项目的主要支持 子项目的首席调查员可能是由其他来源提供的， 包括美国国立卫生研究院的其他来源。为子项目列出的总成本可能 表示该子项目使用的中心基础设施的估计数量， 不是由NCRR赠款提供给次级项目或次级项目工作人员的直接资金。 通过加权集成路径采样法折叠微小蛋白质(Trpage)蛋白质如何折叠是一个科学兴趣问题，因为折叠路径必须覆盖广泛而粗糙的构象，并克服大熵障碍才能达到折叠状态。除了科学上的兴趣，理解蛋白质折叠还有直接和实际的原因：阿尔茨海默病、亨廷顿和帕金森等疾病被认为是由蛋白质错误折叠引起的。使用计算机模拟来探测蛋白质折叠的尝试跨越了过去50年，具有相当大的挑战性。因此，本文利用微小蛋白质的计算折叠来探讨计算模型和方法的准确性和有效性。在这里，我们提出了通过加权集成路径抽样方法折叠三笼微型蛋白质。加权系综方法以前被应用于蛋白质Camodlin，以研究两态系统的跃迁。在那里，这种方法证明了它的有效性，可以实现需要系统爬过令人望而却步的能量障碍的容易处理的罕见过渡。在这里，我们采用并应用蛋白质折叠的方法，其中蛋白质模型必须克服多种能量障碍才能达到折叠状态。我们比较了这种方法的效率与传统分子动力学的强力折叠。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Folding a mini-protein (trpcage) via the Weighted Ensemble Path Sampling Method How proteins fold is a matter of scientific interest because the folding pathway must cover a broad and rough configurational landscape, and overcome large entropic barriers to reach the folded state. Besides the scientific interest, there are direct and practical reasons to understand protein folding: Diseases like Alzheimers, Huntingtons and Parkinsons are proposed to be caused by protein mis-folding. Attempts to use computer simulations to probe protein-folding span the past 50 years, and is quite challenging. Therefore computational folding of mini-proteins is used to probe the accuracy and effectiveness of computational models and methods. Here we present folding the trpcage mini-protein via the Weighted Ensemble Path Sampling method. The Weighted Ensemble method was previously applied to the protein Camodulin, to investigate transitions of a two state system. There, the method demonstrated its usefulness to make tractable rare transitions that require the system to climb over prohibitive energy barriers. Here, we adapt and apply the method for protein-folding, where the protein model must overcome a manifold of energy barriers to reach the folded state. We compare the efficiency of this method to brute force folding via conventional molecular dynamics.