Determining the Effects of Sequence Variation on SARS-CoV-2 Spike Protein through High-Resolution Characterization of Protein Energy Landscapes

每一种蛋白质都是由独特的氨基酸序列定义的，这些氨基酸序列与环境一起决定了它的功能。 今天，由于机器学习，基因组数据库和大量已知结构的进步，我们有能力准确预测蛋白质折叠状态的结构模型，只需给出这个氨基酸序列。 但是序列编码的不仅仅是结构;蛋白质是一个整体，不断地采样其他构象。通过突变或进化，序列的微小变化很少改变折叠结构，但它们可以对行为和功能产生巨大影响。构象多样性和与这种多样性相关的动力学起着重要的作用;蛋白质的这种整体观点解释了微小的遗传变化如何改变表型并驱动进化。因此，尽管最近在预测结构方面取得了进展，但我们仍然无法从序列中预测蛋白质的行为。 为了收集基因组中编码的所有信息，我们必须了解蛋白质序列和整个集合（称为能量景观）之间的关系。一个重要的例子是SARS-CoV-2刺突蛋白的变异体在人群中不断出现-缺乏对这些变化影响的分子理解阻碍了我们对病毒生命周期和病毒进化压力的理解。该提案的影响超出了拟议的研究成果。 PI将继续发展她的职业发展计划，为伯克利的300名博士后研究员建立专门的博士后事务计划（分子和细胞生物学系）。 PI和她的实验室将为当地科学界提供HDX-MS仪器和专业知识，方法学的发展将提高HDX-MS研究的分辨率，超越SARS-CoV-2刺突蛋白。 该奖项的目的是开发和使用新的氢交换方法（HDX-MS），该方法将允许轻松快速地表征蛋白质的能量景观，并确定序列变异的影响。 酰胺氢氘交换是唯一适合于表征蛋白质的能量景观;它是“盲目的”折叠状态和高能量构象和波动敏感。通过对蛋白质同位素包络的时间依赖性变化中的信息进行去卷积，主要研究者（PI）将定义速率曲线（指纹）-一组说明蛋白质整个序列的单个酰胺交换速率。 该指纹是蛋白质在给定条件下能量景观的独特反映。然后，使用完整蛋白质和肽水平HDX-MS的组合，研究人员将进行实验，以表征和量化从天然构象可获得的构象分布。PI和她的团队将使用这些新的发展与传统的HDX-MS一起研究SARS-CoV-2刺突蛋白和分离的受体结合结构域中序列变体的影响，以直接比较其构象集合的变化与观察到的适应性和功能变化。 这些结果将有助于更深入地了解SARS-CoV-2变异体之间的关系及其对病毒及其生命周期的影响。方法的发展将提高HDX-MS研究的分辨率，PI和她的实验室将为当地科学界提供HDX-MS仪器和专业知识。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

Every protein is defined by a unique sequence of amino acids that, together with the environment, dictates its function. Today, thanks to advances in machine learning, genomic data bases, and the large number of known structures, we have the ability to accurately predict a structural model for the folded state of a protein given only this amino-acid sequence. But the sequence encodes more than just the structure; the protein is an ensemble, constantly sampling other conformations. Small changes in sequence, through mutation or evolution, rarely change the folded structure, yet they can have dramatic effects on behavior and function. The conformational diversity and the dynamics associated with this diversity play an important role; this ensemble view of proteins explains how small genetic changes can alter phenotype and drive evolution. Therefore, in spite of the recent advances in predicting structure, we still cannot predict the behavior of a protein from sequence. In order to harvest all of the information encoded in the genome, it is imperative that we understand this relationship between protein sequence and the entire ensemble (referred to as the energy landscape). A critical example of this is the variants of the SARS-CoV-2 spike protein that are continuing to arise in the population — the lack of a molecular understanding of the effects of these changes has impeded our understanding of the effects on the viral lifecycle and the evolutionary pressures on the virus. The proposal has broader impacts beyond the proposed research outcomes. The PI will continue to grow her career development program, establishing a dedicated post-doctoral affairs program for the 300 postdoctoral fellows at Berkeley (Department of Molecular and Cell Biology). The PI and her lab will provide access to HDX-MS instrumentation and expertise to the local scientific community and the methodological developments will enhance the resolution of HDX-MS studies beyond the SARS-CoV-2 spike protein. The objective of this award is to develop and use new hydrogen exchange approaches (HDX-MS) that will allow facile and rapid characterization of a protein’s energy landscape and determine the effects of sequence variation. Amide Hydrogen-Deuterium Exchange is uniquely suited to characterizing a protein’s energy landscape; it is ‘blind’ to the folded-state and sensitive to high-energy conformations and fluctuations. By deconvoluting the information in the time-dependent changes of the isotope envelope of a protein, the Principal Investigator (PI) will define a rate profile (fingerprint) - a set of individual amide exchange rates accounting for the entire sequence of a protein. This fingerprint is a unique reflection of the energy landscape for a protein under the given conditions. Then, using a combination of intact protein and peptide-level HDX-MS, the investigators will carry out experiments to characterize and quantify the distribution of conformations accessible from the native conformation. The PI and her team will use these new developments together with conventional HDX-MS to look at the effect of sequence variants in the SARS-CoV-2 spike protein and the isolated receptor binding domain to directly compare the changes in its ensemble of conformations to observed changes in fitness and function. The results will provide a deeper understanding of the relationship between SARS-CoV-2 variants and their effects on the virus and its lifecycle. The methodological developments will enhance the resolution of HDX-MS studies and the PI and her lab will provide access to HDX-MS instrumentation and expertise to the local scientific community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.