CAREER: Resolving the Influence of Biologically Relevant Microenvironments on Amyloid Aggregation

职业：解决生物学相关微环境对淀粉样蛋白聚集的影响

• 批准号: 2237521
• 负责人: Anne Brown
• 金额: $ 80万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-15 至 2027-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2237521&HistoricalAwards=false
• 关键词: CAREER; Resolving; Influence; Biologically; Relevant

Amyloids are proteins that aggregate into highly ordered structures and exhibit signature aggregation pathways that drive these proteins to functional or cytotoxic activities. Some amyloids, like β-endorphin (βE), are signaling molecules and do not have any known cytotoxic activities. Others, like islet amyloid polypeptide (IAPP) and α-synuclein (αS) participate in both functional and cytotoxic cellular activities. Completing the demonstration of a spectrum of functional to cytotoxic states, amyloid-β (Aβ) is a known cytotoxic amyloid with no clear functional purpose. Taken together, amyloids constitute a very curious class of proteins that are evolutionarily and structurally connected. By studying amyloid aggregation events in membrane environments at the atomistic level, we can identify key molecular properties that drive the spectrum of functionality and cytotoxicity of these peptides. Molecular dynamics (MD) simulations offer a cost-effective and atomistic technique to probe these aggregation events in complex membrane environments that mimic cellular environments. Using the topic of protein-structure function relationship of amyloids, coupled with computational techniques, we will further create accessible, scalable, and sustainable undergraduate research opportunities and K-12 outreach programs that enhance biochemical and data science knowledge to students to prepare them for the workforce. Collectively, systematic investigation of membrane impact on amyloids using cutting-edge simulation techniques will provide essential knowledge on biophysical events that result in essential biological function that can be utilized for materials and drug discovery routes.Notoriously difficult to resolve and work with in vitro and in vivo, amyloid proteins remain a challenge to characterize given their transient, metastable structural folding pathways and a “superficially similar” degree of comparison in microscopy studies. A notable amyloid-world hypothesis has arisen in which the earliest biological information transfer was mediated by amyloid proteins, encrypting environmental information through structural changes to pass onto progeny molecular entities. Given the duality of multifaceted functionality and cytotoxicity of amyloids and their role in biological information transfer, it is crucial to understand the influence of microenvironments on the biophysics of amyloid aggregation. We hypothesize that lipid membrane composition and glycosaminoglycans presence will impact and remodel aggregation events of amyloids. Relatedly, amyloid structural morphologies and sequence-specific motifs will indicate position on the spectrum of functional to cytotoxic amyloids. Utilizing cutting-edge molecular dynamics (MD) simulations, that include classical, replica exchange, and polarizable MD, we will simulate aggregation events of oligomeric amyloids in various membrane environments. Conformational dynamics will be explored utilizing transition networks and Markov state models. This proposed work will push the capabilities of MD simulations to atomistically explore protein aggregation pathways and interconnect various amyloidogenic species (β-endorphin (βE, islet amyloid polypeptide (IAPP), α-synuclein (αS), and amyloid-β (Aβ)), to biological implications and phenomena. Utilization of data-rich, computational methods will further the integrated data and research literacy education components of this work given the ability to connect computational and algorithmic thinking with biology via local, regional, and global education programs that enhance the computational skillsets of K-12 students, undergraduates, and the 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.

淀粉样蛋白是聚集成高度有序结构的蛋白质，并表现出驱动这些蛋白质发挥功能或细胞毒性活性的特征性聚集途径。一些淀粉样蛋白，如β-内啡肽（β E），是信号分子，没有任何已知的细胞毒性活性。其他如胰岛淀粉样多肽（IAPP）和α-突触核蛋白（α S）参与功能性和细胞毒性细胞活动。淀粉样蛋白-β（A β）是一种已知的细胞毒性淀粉样蛋白，没有明确的功能目的，从而完成了一系列功能性至细胞毒性状态的证明。总的来说，淀粉样蛋白构成了一类非常奇怪的蛋白质，它们在进化和结构上都有联系。通过在原子水平上研究膜环境中的淀粉样蛋白聚集事件，我们可以确定驱动这些肽的功能和细胞毒性谱的关键分子特性。分子动力学（MD）模拟提供了一种具有成本效益和原子的技术来探测这些聚集事件在复杂的膜环境，模仿细胞环境。利用淀粉样蛋白的蛋白质结构功能关系的主题，再加上计算技术，我们将进一步创造可访问的，可扩展的，可持续的本科生研究机会和K-12外展计划，提高生物化学和数据科学知识的学生准备他们的劳动力。总的来说，使用尖端的模拟技术系统地研究膜对淀粉样蛋白的影响，将提供有关生物物理事件的基本知识，这些生物物理事件导致可用于材料和药物发现路线的基本生物功能。众所周知，淀粉样蛋白难以在体外和体内解析和工作，由于其短暂性，亚稳态结构折叠途径和显微镜研究中的"表面相似"程度的比较。一个值得注意的淀粉样世界假说已经出现，其中最早的生物信息传递是由淀粉样蛋白介导的，通过结构变化加密环境信息传递给后代分子实体。鉴于淀粉样蛋白的多方面功能和细胞毒性的双重性及其在生物信息传递中的作用，了解微环境对淀粉样蛋白聚集的生物物理学的影响至关重要。我们假设脂质膜组成和糖胺聚糖的存在将影响和重塑淀粉样蛋白的聚集事件。相关地，淀粉样蛋白结构形态和序列特异性基序将指示功能性淀粉样蛋白至细胞毒性淀粉样蛋白谱上的位置。利用尖端的分子动力学（MD）模拟，包括经典的，副本交换，和极化MD，我们将模拟聚合事件的寡聚淀粉样蛋白在各种膜环境。构象动力学将探讨利用过渡网络和马尔可夫状态模型。这项拟议的工作将推动MD模拟的能力，以原子方式探索蛋白质聚集途径，并将各种淀粉样物质（β-内啡肽（β E），胰岛淀粉样多肽（IAPP），α-突触核蛋白（α S）和淀粉样蛋白-β（A β））与生物学意义和现象联系起来。利用数据丰富的计算方法，将进一步整合数据和研究素养教育的组成部分，这项工作的能力，连接计算和算法思维与生物学通过地方，区域和全球教育计划，提高K-12学生的计算技能，本科生，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。