CAREER: Selectively Reprogramming Proteases through the High-Throughput Discovery of Functional Protein-Protein Interactions.

职业：通过功能性蛋白质-蛋白质相互作用的高通量发现选择性地重编程蛋白酶。

• 批准号: 2237629
• 负责人: Carl Denard
• 金额: $ 60.72万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-01 至 2028-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2237629&HistoricalAwards=false
• 关键词: CAREER; Selectively; Reprogramming; Proteases; through

Proteases are enzymes that cleave peptide bonds in proteins. They abound in all organisms and play key roles in regulating cellular processes. If their activity is impaired, diseases can arise. These range from infectious diseases to cancer and neurodegeneration. The main research objective of this project is to discover and redesign proteinaceous molecules that can reprogram proteases. The major educational objective is to develop a STEM comic series on synthetic biology targeted at K-5 students. Protease dysregulation is a disease indicator, as proteases play central roles in bacterial and viral pathogenicity. An experimental and computational framework is proposed to understand how proteases work and how to reprogram them. This will require the development of function-centric technologies to discover protein-based binders that can reprogram a protease’s catalytic activity and substrate specificity. Aim 1 is to isolate selective, potent inhibitory and stimulatory nanobodies from a synthetic nanobody (Nb) library against proteases from four groups, including human protease targets. Aim 2 is to leverage deep learning to accelerate modulator discovery by designing machine learning-optimized Nb libraries using Nb sequence-function data. Aim 3 is to map the functional landscape of insulin-degrading enzyme (IDE) through Nb-mediated protein-protein interactions (PPIs) and protease engineering. Deep sequencing data analysis will elucidate the sequence-function landscape for novel functional PPIs.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.

蛋白酶是切割蛋白质中的肽键的酶。它们大量存在于所有生物体中，并在调节细胞过程中发挥关键作用。 如果他们的活动受到损害，疾病可能会出现。这些疾病从传染病到癌症和神经变性。该项目的主要研究目标是发现和重新设计能够重编程蛋白酶的蛋白质分子。 主要的教育目标是开发一个针对K-5学生的合成生物学STEM漫画系列。蛋白酶失调是一种疾病指标，因为蛋白酶在细菌和病毒致病性中起核心作用。提出了一个实验和计算框架，以了解蛋白酶如何工作，以及如何重新编程它们。这将需要开发以功能为中心的技术，以发现可以重新编程蛋白酶的催化活性和底物特异性的基于蛋白质的结合剂。目的1是从合成纳米抗体（Nb）文库中分离针对来自四组蛋白酶（包括人蛋白酶靶标）的选择性、有效抑制性和刺激性纳米抗体。目标2是利用深度学习，通过使用Nb序列-功能数据设计机器学习优化的Nb库来加速调制器发现。目的三是通过铌介导的蛋白质-蛋白质相互作用（PPI）和蛋白酶工程构建胰岛素降解酶（IDE）的功能图谱。深度测序数据分析将阐明新型功能性PPI的序列-功能前景。该奖项反映了NSF的法定使命，并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，被认为值得支持。