Manipulating and predicting the unfolded ensembles of disordered proteins

项目总结 固有无序蛋白(IDPs)的物理性质影响其正(功能)和负(功能) (致病)在细胞功能中的作用。然而，尽管付出了巨大的努力，我们仍然缺乏对 控制给定的多肽链序列是否将采用扩展的或 生理条件下的塌陷构象集合--以及塌陷如何影响 蛋白质的功能。Sosnick和Clark实验室已经形成了一项合作，专门开发这一技术 理解。该项目包括对境内流离失所者的实验研究，并与新的数据分析紧密结合。 程序和计算建模工具。这个项目建立在我们最近与“PNT”的发现之上，PNT是一个334 在生理条件下采用扩展构象集合的残留物IDP 由自我避免的随机行走近似，尽管有氨基酸含量，根据 当前的范式，应该会导致一种崩溃的、自我关联的状态。我们假设目前的模型不能 由于当前关于哪些序列模式的知识差距，预测PNT的行为，而不是全局的 层序组成，导致崩塌。我们建议，偏离扩展状态，例如，采用 塌陷的球体，是由于特定的序列模式，包括局部延伸的疏水残基。我们 将通过重新排列PNT的氨基酸序列来检验这一假说，以诱导折叠，以及 同样，重组麦芽糖结合蛋白(MBP)的氨基酸序列以促进其扩增 变性状态，我们最近展示了它是高度崩溃的。我们将使用生物物理电池 方法(SAXS，氢-氚交换，核磁共振)测量局部和全球崩溃的程度， 评估构象集合对序列顺序的细微变化的敏感性，以及 崩塌与氢键的关系。我们将确定哪些疏水性等级会产生 对多肽链崩溃的实验结果的最佳预测，并使用洗牌的效果 对模拟进行参数化。最后，我们将在体内测试改变IDP塌陷对蛋白质功能的影响， 革兰氏阴性杆菌表面高效分泌自身转运蛋白的研究 细菌。我们的总体目标是准确地预测用户输入的氨基酸的构象集合 顺序和溶剂条件。

PROJECT SUMMARY The physical properties of intrinsically disordered proteins (IDPs) affect their positive (functional) and negative (disease-causing) roles in cell function. Yet despite intense effort, we still lack a predictive understanding of the physical properties that govern whether a given polypeptide chain sequence will adopt an expanded or collapsed conformational ensemble under physiological conditions – and by extension, how collapse affects protein function. The Sosnick and Clark labs have formed a collaboration to develop precisely this understanding. This project consists of experimental studies of IDPs tightly integrated with new data analysis procedures and computational modeling tools. This project builds on our recent findings with “PNt”, a 334 residue IDP that under physiological conditions adopts an expanded ensemble of conformations well approximated by a self-avoiding random walk, despite having an amino acid content that, according to the current paradigm, should lead to a collapsed, self-associated state. We hypothesize that current models fail to predict the behavior of PNt due to current knowledge gaps regarding which sequence patterns, beyond global sequence composition, lead to collapse. We propose that deviations from an expanded state, e.g., adopting a collapsed globule, are due to specific sequence patterns including local stretches of hydrophobic residues. We will test this hypothesis by reordering (“shuffling”) the amino acid sequence of PNt to induce collapse, and likewise shuffle the amino acid sequence of maltose binding protein (MBP) to promote expansion of its denatured state, which we recently demonstrated is highly collapsed. We will use a battery of biophysical methods (SAXS, hydrogen-deuterium exchange, NMR) to measure the extent of local versus global collapse, assessing the sensitivity of conformational ensembles to subtle changes in sequence order, and the relationship between collapse and hydrogen bonding. We will determine which hydrophobicity scales yield the best predictions of experimental results for polypeptide chain collapse, and use the effects of shuffling to parameterize simulations. Finally, we will test the impact of altering IDP collapse on protein function in vivo, specifically the efficient secretion of autotransporter virulence proteins to the surface of Gram-negative bacteria. Our overall goal is to accurately predict the conformational ensemble for a user-inputted amino acid sequence and solvent condition.