Collaborative Research: Dynamics of surfactant - amyloid-beta protein interactions during self-assembly

蛋白质分子在一种称为“聚集”的过程中聚集是细胞生物学中的一个常见问题。有一种蛋白质聚集会导致一种叫做“淀粉样蛋白”的特殊结构，被认为在包括阿尔茨海默病在内的许多神经退行性疾病中起着关键作用。最近，蛋白质淀粉样蛋白也与正常的细胞功能有关。在聚集过程中会形成各种各样的聚集体结构，其中许多会引起特定的生物反应。因此，了解聚集的机制对人类健康至关重要。淀粉样蛋白的形成受到生物表面活性分子的影响，这些分子与许多淀粉样蛋白相关。在拟议的项目中，首席研究员和一组合作者将使用实验、计算机模拟和数学分析来了解表面活性物质如何调节淀粉样蛋白聚集形成特定的聚集物种。这将改变我们对这些相互作用的理解，这些相互作用在阿尔茨海默病中发挥作用。这一科学努力还将涉及许多学生，他们不仅将学习新的研究领域，还将为数据收集和结果解释做出贡献。与阿尔茨海默氏症相关的一种名为淀粉样β的蛋白质的自我关联涉及到以依赖于核的方式从其固有的无序单体形式转变为组织良好的纤维结构。在形成的聚集体中，低分子量低聚物已成为生理上重要的物种。形成的低聚物不一定是纤维形成途径的专有中间体，它们可以沿着交替的“非途径”形成，这导致了许多不同的淀粉样β蛋白结构应变。许多因素都可以诱发非途径产物。在这些因素中，生物表面活性剂(SA)产生的界面具有生理相关性，因为它们与淀粉样β蛋白具有永久的联系。首席研究人员实验室的最新发现表明，非酯化脂肪酸SA以浓度依赖的方式诱导途径外或途径上的聚集。研究人员假设，SA的浓度依赖相变调节淀粉样β聚集途径，以产生不同的寡聚体。在这项工作中，一个合作团队将以两个特定的目标来验证这一假说：Aim 1将使用各种阴离子SA从生物物理学的角度研究淀粉样β蛋白和SA之间的相互作用，而Aim 2将使用数值模拟和降阶数学分析来模拟由于淀粉样β蛋白-SA相互作用而导致的寡聚体的时间演化。一种涉及实验生物物理、模拟和数学分析的跨学科方法，以及实验(目标1)和模拟(目标2)之间的协同反馈，将为深入了解淀粉样β蛋白和SAS之间的异型相互作用提供见解，并将弥合该领域现有的知识差距。考虑到非途径聚集体的功能效应与其各自的形态有关，了解淀粉样β-SA相互作用的物理化学性质对于破解淀粉样蛋白相关的细胞过程将具有至关重要的意义。这项工作还将有助于更好地了解涉及淀粉样蛋白的更大、更复杂的反应网络中的聚集路径，然后可以用来设计未来的干预策略。这项拟议的项目将对南密西西比大学(USM)、弗吉尼亚联邦大学(VCU)和蒙特克莱尔州立大学(MSU)这三所大学的本科生和研究生的科学和教育产生更广泛的影响，分别涉及分子生物物理学、计算系统生物学和数学生物学领域。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Clumping of protein molecules in a process called "aggregation" is a common problem in cellular biology. One kind of protein aggregation leads to a specific structure of the clumps called "amyloids" and is thought to play a key role in many neurodegenerative diseases including Alzheimer's disease. Recently, protein amyloids have also been associated with normal cellular functions. A wide variety of aggregate structures are formed during aggregation, and many of these cause a specific biological response. Hence, understanding the mechanisms of aggregation is critical for human health. Amyloid formation is influenced by biological surfactant molecules, which associate many amyloid proteins. In the proposed project, the principal investigator along with a team of collaborators will use experiments, computer simulations, and mathematical analysis to understand how surfactants modulate amyloid protein aggregation to form specific aggregate species. This will transform our understanding of these interactions which play a role in Alzheimer's disease. This scientific endeavor will also involve many students, who will not only learn new areas of research but will also contribute towards data collection and interpretation of results.Self-association of a protein called amyloid beta, associated with Alzheimer's disease, involves the conversion from its intrinsically disordered, monomeric form to well-organized, fibrillar structures in a nucleation-dependent manner. Among the aggregates formed, the low-molecular weight oligomers have emerged to be physiologically important species. The oligomers formed need not be the obligate intermediates of the fibril formation pathway, and they could be formed along alternate "off-pathways", which result in many distinct structural strains of amyloid beta. Many factors can induce off-pathway products. Among these factors, interfaces generated by biological surfactants (SAs) are physiologically relevant due to their perpetual association with amyloid beta. Recent findings from the principle investigator's lab indicate that non-esterified fatty acid SAs induce off- or on- pathway aggregates in a concentration dependent manner. The investigators hypothesize that concentration-dependent phase transitions of SAs modulate amyloid beta aggregation pathways to generate distinct oligomers. In this work, a collaborative team will test the hypothesis with two specific aims: Aim 1 will investigate biophysically the interactions between amyloid beta and SAs using a variety of anionic SAs, and Aim 2 will model temporal evolution of oligomers as a result of amyloid beta-SA interactions using numerical simulations and reduced order mathematical analysis. An interdisciplinary approach involving experimental biophysics, simulation and mathematical analysis with a synergistic feedback between the experiments (Aim 1) and simulations (Aim 2) will provide insights into the heterotypic interactions between amyloid beta and SAs and will bridge the existing knowledge gap in the field. Considering that the functional effects of off-pathway aggregates are related to their respective morphologies, understanding the physiochemical properties of amyloid beta-SA interactions will be of paramount significance in deciphering amyloid-related cellular processes. This work will also help in a better understanding of aggregation pathways in a larger, more complex network of reactions involving amyloids, which can then be utilized to design intervention strategies in the future. The proposed project will have broader impacts on science and education for undergraduate and graduate students from the three institutions of University of Southern Mississippi (USM), Virginia Commonwealth University (VCU), and Montclair State University (MSU) spanning the areas of molecular biophysics, computational systems biology and mathematical biology respectively.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.