Computational Studies of Model Systems for Protein Unfolded States

虽然蛋白质的展开状态以前被认为在很大程度上是随机的，但特定的证据表明 结构正在积累。即使在低种群中，这种类型的排序也可能直接影响蛋白质 稳定性、折叠机制和速率，以及错误折叠和聚集，这些都与许多 人类疾病。在大多数情况下，残存结构的弱性和低种群的错折 生理条件下的状态排除了直接和详细地描述这些集合的可能性 实验技术。模拟已经开始为实验提供补充数据，因为它们 可以在大多数人无法获得的时间尺度上提供单分子分辨率的结构细节 实验。然而，由于多种原因，模拟在许多重要情况下都会失败。 该提案概述了模拟算法和力场的持续发展，以实现成功 在展开状态研究中的应用，并通过以下方法获得的实验数据直接验证 已建立的合作关系。重点放在构象取样上；构象取样是 该项目涉及开发一种新的抽样方法，以提供改进的收敛 集成数据，显式包含溶剂，大大降低了计算成本。 将在不同复杂性的几个模型系统上进行仿真。在每种情况下，具体说明 突变将探测被假设参与决定结构或稳定性的相互作用 原住民的。其他突变体探测到我们在 展开状态。这些研究将为这些重要的模型系统提供有用的见解，并将 就我们的力场和采样方法的性能提供有价值的和关键的反馈。 下一阶段的研究涉及对每个模型系统的展开系综进行表征，以及 产生关于任何残留结构的性质的可实验测试的假说。对于每个 模型系统，最近的实验表明，在展开状态下可能存在残馀结构，并且我们的 模拟将为解释这些数据提供重要的模型。关于展开的更多研究 通过取代柔性甘氨酸和刚性甘氨酸来实现折叠中的状态和熵的作用 与丙氨酸结合，考察其对折叠自由能和展开态熵的影响。

While unfolded states of proteins were previously thought to be largely random, evidence of specific structure is accumulating. Even at low populations this type of ordering could have direct bearing on protein stability, folding mechanism, and rate, as well as the misfolding and aggregation that are implicated in many human disorders. In most cases, the weak nature of the residual structure and low populations of misfolded states under physiological conditions preclude direct and detailed characterization of these ensembles using experimental techniques. Simulations have begun to provide data complementary to experiments, since they can provide structural detail with single molecule resolution on a time scale inaccessible to most experiments. However, simulations fail in many important cases for multiple reasons. This proposal outlines continued development of simulation algorithms and force fields to enable successful application to the study of unfolded states, with direct validation against experimental data obtained through established collaborations. A strong emphasis is placed on conformational sampling; a major component of the project involves development of a novel sampling approach that provides improved convergence of ensemble data with explicit inclusion of solvent at a significantly reduced computational cost. Simulations will be performed on several model systems of varying complexity. In each case, specific mutations will probe interactions that are hypothesized to be involved in determining the structure or stability of the native fold. Other mutants probe the effect on stability of interactions that we have observed in the unfolded state. These studies will provide useful insight into these important model systems, and will also provide valuable and critical feedback on the performance of our force fields and sampling methods. The next phase of the research involves characterization of unfolded ensembles for each model system, and generation of experimentally testable hypotheses about the nature of any residual structure. For each of the model systems, recent experiments suggest that residual structure may exist in the unfolded state, and our simulations will provide important models for interpretation of this data. Additional studies of the unfolded state and the role of entropy in folding will be performedthrough replacement of flexible glycine and rigid proline with alanine, investigating the effect on unfolded state entropy and free energy of folding.