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Rational Design and Fundamental Understanding of Multimodal Amyloid Probes

多模式淀粉样蛋白探针的合理设计和基本理解

基本信息

批准号：
2107619
负责人：
Jie Zheng
金额：
$ 36.2万
依托单位：
University of Akron
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-07-01 至 2025-06-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2107619&HistoricalAwards=false
关键词：
Rational Design Fundamental Understanding Multimodal

项目摘要

The hallmark of many debilitating diseases, such as Alzeimer’s disease (AD) and type II diabetes (T2D), is the presence of abnormal masses/aggregates of proteins termed “amyloids”. These amyloids, in which composition is disease dependent, are generally considered to be ideal markers for disease diagnosis and therapeutic intervention. Unfortunately, existing probes are limited in that they are only able to detect the presence of a single targeted amyloid protein. This project will develop a new class of generic, multiple-mode, multi-target amyloid probes that will detect a wide variety of proteins associated with different amyloid diseases. Design principles for the multimodal probes can be transformed to numerous molecular-recognition applications for targeted drug therapy, biomarker detection, and disease diagnostics (e.g., cancers and COVID-19). The proposed multi-disciplinary research activities will provide diverse training for students at all levels, especially from underrepresented and low-income families. The students will develop knowledge and skills in data mining, molecular simulations, neuroscience, and lab-on-chip techniques in close relation to public health problems. Finally, the integrated educational and research activities will enrich the curriculum of the Corrosion Engineering program at the University of Akron.The overall objectives of this project are to (1) fully explore, identify, and engineer – with both data-driven simulations and experiments – a new family of AIE@βPs (an aggregation-induced emission (AIE) molecule conjugated with small β-sheet-forming peptides (βPs)) probes capable of early and enhanced detection of multiple pathological aggregates and co-aggregates formed by the same and different amyloid proteins, which co-exist in human body fluids across different amyloid diseases and (2) conduct fundamental sequence-structure-recognition studies on these multi-mode, multiple-target AIE@βPs probes. The AIE molecule targets the aggregated amyloids and avoids the aggregation-induced quenching, while βPs target the β-structures of amyloid aggregates via specific β-sheet interactions. The project’s objectives will be achieved via three tasks: (1) develop a machine-learning model, combined with molecular simulations and biophysical experiments, to screen, identify, and validate a library of βPs capable of self-assembling into β-sheet structures and cross-interacting with both Aβ (associated with AD) and hIAPP (associated with T2D); (2) design and synthesize a series of AIE@βPs probes to detect Aβ, hIAPP, and hybrid Aβ-hIAPP species at different aggregation states for demonstrating “conformational-specific, sequence-independent” mechanisms via synergetic AIE- and βPs-induced binding modes; and (3) transform AIE@βPs probes into different amyloid sensors via surface immobilization by controlling their packing structures, densities, and patterns of AIE@βPs. In parallel, multiscale molecular simulations will be conducted to study the structures, dynamics, and interactions of βPs and AIE@βPs with amyloid aggregates in solution and on surfaces, which will be correlated with amyloid recognition mechanisms of AIE@βPs by experiments. If successful, this work will provide new design principles and sensor systems for early amyloid detection beyond few available today.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.

许多使人衰弱的疾病，如阿尔茨海默病（AD）和II型糖尿病（T2 D）的标志是存在称为“淀粉样蛋白”的蛋白质的异常团块/聚集体。这些淀粉样蛋白的组成是疾病依赖性的，通常被认为是疾病诊断和治疗干预的理想标志物。不幸的是，现有的探针是有限的，因为它们只能检测到一个单一的目标淀粉样蛋白的存在。该项目将开发一类新的通用、多模式、多靶点淀粉样蛋白探针，用于检测与不同淀粉样蛋白疾病相关的各种蛋白质。多模式探针的设计原理可以转化为用于靶向药物治疗、生物标志物检测和疾病诊断的许多分子识别应用（例如，癌症和COVID-19）。拟议的多学科研究活动将为各级学生，特别是来自代表性不足和低收入家庭的学生提供多样化的培训。学生将发展与公共卫生问题密切相关的数据挖掘，分子模拟，神经科学和芯片实验室技术的知识和技能。最后，综合教育和研究活动将丰富阿克伦大学腐蚀工程项目的课程。本项目的总体目标是（1）充分探索，识别，通过数据驱动的模拟和实验，设计一个新的AIE@β P系列（与小β-折叠形成肽（βPs）缀合的聚集诱导发射（AIE）分子）探针，其能够早期和增强检测多种病理性聚集体和共由相同和不同的淀粉样蛋白形成的聚集体，其在不同的淀粉样疾病中共存于人体体液中，以及（2）对这些多模式、多靶点AIE@βPs探针进行基本的序列-结构-识别研究。AIE分子靶向聚集的淀粉样蛋白并避免聚集诱导的淬灭，而βPs通过特异性β折叠相互作用靶向淀粉样蛋白聚集体的β结构。该项目的目标将通过三项任务实现：（1）开发一个机器学习模型，结合分子模拟和生物物理实验，筛选，鉴定和验证能够自组装成β折叠结构并与Aβ交叉相互作用的βPs库，（与AD相关）和hIAPP（与T2 D相关）;（2）设计合成一系列AIE@βPs探针，用于检测Aβ、hIAPP、和不同聚集状态的杂合Aβ-hIAPP物种，通过协同AIE和β Ps诱导的结合模式证明“构象特异性，序列无关性”机制;（3）通过控制AIE@βPs的堆积结构、密度和模式，将AIE @ βPs探针通过表面固定化转化为不同的淀粉样蛋白传感器。与此同时，我们将进行多尺度分子模拟，研究βPs和AIE@βPs在溶液和表面上的结构、动力学以及与淀粉样蛋白聚集体的相互作用，并通过实验研究AIE@βPs识别淀粉样蛋白的机制。如果成功，这项工作将提供新的设计原则和传感器系统，早期淀粉样蛋白检测超越少数可用today.This奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。