Foldamers: Novel Ligands for Diverse Protein Surfaces

描述（由申请人提供）：本申请建立在我们实验室最近结果的基础上，该结果详细描述了用于设计β-肽的一般策略，所述β-肽在水中是高度14-螺旋的并且以高亲和力结合蛋白质表面，例如hDM 2的p53 AD相互作用结构域。在目标1中，我们探索了有助于14-螺旋在水中稳定性的结构特征和14-螺旋β-肽beta53-1识别蛋白质表面的能力。我们将完成一个广泛的“主-客”分析，将所有的蛋白质和选定的非蛋白质侧链分类为14-螺旋稳定，不稳定，或中性，产生一个数据库的位置依赖性，14-螺旋倾向在水中;确定β 53 -1的NMR溶液结构，以支持主-客数据和指导未来的设计工作;并探索是否可以通过引入环状ACHC残基来改善β 53 -1的稳定性或亲和力。在目标2中，我们基于目标1的结果，为威胁人类健康、国家安全或两者兼而有之的3种病毒的包膜糖蛋白设计β-肽配体：HIV、人呼吸道合胞病毒（HRSV）和引起严重急性呼吸综合征（SARS-CoV）的冠状病毒。目标2中的实验将在高度相关和易于处理的系统中验证我们的β肽设计策略，并可能为未来的药物开发提供线索。在目标3中，我们开发了合成、分析和筛选β-肽组合文库的方法，并使用它们来优化目标1和2中鉴定的β-肽的亲和力（并使大小最小化）。该目标还包括鉴定细胞可渗透的beta53-1文库成员的实验，这些信息将指导用于其他经验证的靶标的β-肽配体的设计。总之，本申请中的实验将提供配体设计的基本信息，并有助于实现化学生物学研究中最核心和关键（尚未实现）的目标之一，即快速鉴定大量潜在非酶蛋白靶点的高亲和力配体。

DESCRIPTION (provided by applicant): This application builds on a foundation of recent results from our laboratory detailing a general strategy for the design of beta-peptides that are highly 14-helical in water and bind with high affinity to protein surfaces, such as the p53AD interaction domain of hDM2. In Aim 1 we explore the structural features that contribute to 14-helix stability in water and the ability of the 14-helical beta-peptide beta53-1 to recognize protein surfaces. We will complete an extensive "host-guest" analysis that will classify all proteinogenic and selected non-proteinogenic side chains as 14-helix stabilizing, destabilizing, or neutral, generating a database of position-dependent, 14-helix propensities in water; determine the NMR solution structure of beta53-1 to support the host-guest data and guide future design efforts; and explore whether the stability or affinity of beta53-1 can be improved by introduction of cyclic ACHC residues. In Aim 2 we build on the results of Aim 1 to design beta-peptide ligands for the envelope glycoproteins of 3 viruses that threaten human health, national security, or both: HIV, human respiratory syncytial virus (HRSV), and the coronavirus that causes severe acute respiratory syndrome (SARS-CoV). The experiments in Aim 2 will validate our betapeptide design strategy in a system that is highly relevant and tractable, and will likely provide leads for future drug development. In Aim 3 we develop methods to synthesize, analyze, and screen beta-peptide combinatorial libraries, and use them to optimize the affinities (and minimize the size) of beta-peptides identified in Aims 1 and 2. This aim also includes an experiment to identify cell-permeable beta53-1 library members, information that will guide design of beta-peptide ligands for additional validated targets. Taken together, the experiments in this application will provide fundamental information on ligand design and help achieve 1 of the most central and critical (yet unmet) goals of chemical biology research, the rapid identification of high affinity ligands for the vast array of potential non-enzymatic protein targets.