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.

蛋白酶是裂解蛋白质中肽键的酶，它们在调节细胞过程中发挥着关键作用，如果它们的活性受损，就会出现从传染病到癌症和神经退行性疾病的疾病。该项目是发现和重新设计可以重新编程蛋白酶的蛋白质分子，主要教育目标是为 K-5 学生开发合成生物学 STEM 漫画系列，因为蛋白酶发挥作用，蛋白酶失调是一种有针对性的疾病指标。提出了一个实验和计算框架来了解蛋白酶如何工作以及如何对其进行重新编程，这将需要开发以功能为中心的技术来发现可以重新编程蛋白酶催化活性的蛋白质结合剂。目标 1 是从合成纳米抗体 (Nb) 库中分离出针对四组蛋白酶（包括人类蛋白酶靶标）的选择性、有效的抑制性和刺激性纳米抗体。目标 3 是利用 Nb 序列功能数据设计机器学习优化的 Nb 库，利用深度学习来加速调节剂的发现。目标 3 是通过 Nb 介导的蛋白质-蛋白质相互作用 (PPI) 绘制胰岛素降解酶 (IDE) 的功能图谱。 ）和蛋白酶工程。深度测序数据分析将阐明新型功能性 PPI 的序列功能景观。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查进行评估，被认为值得支持。标准。