Oligomerization, confinement and the folding barrier

描述（由申请人提供）：由于模拟和实验的局限性，对蛋白质折叠的最终理解可能来自于通过实验广泛验证和测试的详细模拟的耦合方法。然而，由于所涉及的长时间尺度以及详细的原子模型的困难和复杂性，开发能够定量地与实验动力学相联系的模拟方法仍然是一个巨大的理论挑战。最后，通过模拟定量预测溶液中蛋白质折叠实验动力学的能力，新的挑战出现了：理解生物学相关背景下的折叠，例如天然非结构化蛋白质和密闭空间中的折叠。在这里，我们提出了新的第二代分布式计算方法来解决这些挑战，并将这些方法应用于与蛋白质如何在溶液中自组装相关的问题，以及天然非结构化蛋白质和蛋白质在密闭空间中折叠的生物学相关背景，作为重要生物学背景（如核糖体、伴侣蛋白和细胞质）的模型。虽然蛋白质折叠本身已经进行了多年的计算研究，但我们的工作与其他方法的不同之处是：(1)使用新颖的分布式计算方法，使用详细的、全原子的、明确的溶剂模型来模拟长时间尺度的动力学；(2)应用这些详细模型来解决天然非结构化蛋白质和限制的生物学背景下的折叠问题。与实验的定量比较对于我们的计算方法的测试和更大的影响都是至关重要的，这种实验合作是通过一系列合作提出的。最后，提出的工作应该对我们对几种蛋白质相关疾病的基本理解产生影响，例如涉及p53四聚体和激活结构域突变的癌症。此外，通过了解密闭空间中折叠的本质，人们将深入了解蛋白质在体内折叠的本质，这将是我们理解蛋白质折叠及其与生物学和生物医学问题联系的重要一步。

DESCRIPTION (provided by applicant): Due the limitations of both simulation and experiment, an ultimate understanding of protein folding will likely come from a coupled approach of detailed simulations extensively validated and tested by experiment. However, developing simulation methodology which can quantitatively connect with experimental kinetics still remains a great theoretical challenge, due to the long timescales involved and the difficulties and complexities of detailed, atomistic models. Finally, with the ability of simulation to quantitatively predict experimental kinetics for protein folding in solution, new challenges emerge: understanding folding in biologically relevant contexts, such as natively unstructured proteins and folding in confined spaces. Here, we propose new, second generation distributed computing methods to tackle these challenges and the application of these methods to questions related to how proteins self-assemble in solution, as well as in the biologically relevant contexts of natively unstructured proteins and proteins folding in confined spaces as a model for important biological contexts, such as ribosomes, chaperones, and the cytosol. While protein folding has itself been studied computationally for many years, our work differs from other approaches in (1) its use of novel distributed computing methods for simulating long time scale kinetics using detailed, fully atomistic, explicit solvent models and (2) the application of these detailed models to address questions of folding in the biological contexts of natively unstructured proteins and confinement. A quantitative comparison to experiment is critical for both the testing and greater impact of our computational methods and such experimental collaborations are proposed via a series of collaborations. Finally, the proposed work should have an impact on our basic understanding of several protein- related diseases, such as cancers involved in mutations of the tetramerization and activation domains of p53. Also, by understanding the nature of folding in confined spaces, one would gain insight into the nature of protein folding in vivo, which would be an important next step in our understanding of protein folding and its connection to biology and biomedical questions.