CAREER: Combining Research and Education via the Exploration of Peptide-Lipid Binding and Aggregation

通过这个奖项，化学学部生命过程化学项目资助了马里兰大学帕克分校的Silvina Matysiak博士，研究脂质成分如何影响脂质膜上肽的自组装途径。该项目涉及使用计算方法来确定在几种淀粉样蛋白源性肽的情况下，脂质头基团的化学作用是如何促进肽招募、错误折叠和聚集的。这些研究将提供促进或阻碍肽自组装的重要条件的基本信息，并负责最终聚集体的形态。该项目的结果可能用于了解神经元中蛋白质错误折叠如何导致神经元功能障碍。作为该项目的一部分，将创建几个工具箱来教育高中和本科水平的家长和学生，分子相互作用在日常世界中的重要性。为了实现这一目标，活细胞的实时视频或动画将与蛋白质的交互式动手建模相结合。在理解蛋白质如何在细胞膜上错误折叠和聚集方面存在根本性的空白。本项目涉及一项计算研究，旨在阐明膜组成如何调节淀粉样肽聚集。对膜表面多肽聚集背后的驱动力的深入了解将对从生物材料到生物技术的许多学科产生影响。这些方法涉及在本项目上下文中对先前开发的粗粒度模型进行扩展。该项目旨在1)研究肽-脂质氢键在肽聚集中的作用，2)量化静电相互作用在形成聚集途径中的影响，3)剖析多价离子在脂质结构域形成中的影响以及这如何影响肽能量景观，4)表征膜物理性质的变化如何改变肽聚集行为。在这个奖项中开发的计算模型将免费向公众提供。

With this award, the Chemistry of Life Processes Program in the Chemistry Division is funding Dr. Silvina Matysiak from The University of Maryland, College Park to investigate how lipid composition affects peptide self-assembly pathways on a lipid membrane. The project involves the use of computational methods to establish how the chemistry of a lipid headgroup promotes peptide recruitment, misfolding and aggregation in the cases of several amyloidogenic peptides. These studies will provide fundamental information on vital conditions that promote or impede peptide self-assembly and that are responsible for the morphology of the resulting aggregates. The results of this project may be used to understand how protein misfolding in neurons may lead to neuronal dysfunction. As part of the project, several toolboxes will be created to teach parents and students at the high school and undergraduate levels, the importance of molecular interactions in the everyday world. In order to achieve this goal, real-time videos of living cells or animations will be combined with interactive hands-on modeling of proteins.There is a fundamental gap in understanding how proteins misfold and aggregate on cellular membranes. This project involves a computational investigation that aims at elucidating how membrane composition modulates amyloid peptide aggregation. A deeper understanding of the driving forces behind peptide aggregation on membranous surfaces would have impact on a number of disciplines ranging from biomaterials to biotechnology. The approaches involve an expansion of a previously developed coarse-grained model in the context of this project. The project aims to 1) study the role of peptide-lipid hydrogen bonds in peptide aggregation, 2) quantify the impact of electrostatic interactions in shaping aggregation pathways, 3) dissect the influence of multivalent ions in lipid domain formations and how this affects peptide energy landscapes and 4) characterize how changes in a membrane's physical properties can modify peptide aggregation behavior. The computational models developed in this award will be made freely available to the public.