Computational Studies on the Modulation of Peptide-lipid Interactions by Glycosaminoglycans

在化学部生命过程化学（CLP）项目的支持下，来自马里兰州大学的SilvinaMatysiak将研究在模拟细胞外基质的环境中促进或阻碍淀粉样蛋白形成的分子条件。细胞外基质是一个复杂的蛋白质和碳水化合物的网格，它连接到它周围的细胞，将它们保持在一起形成组织。淀粉样蛋白是蛋白质沉积物/聚集体。淀粉样蛋白形成是许多正常生物过程和神经退行性疾病（如阿尔茨海默病）中的关键因素。碳水化合物和细胞膜表面在调节淀粉样蛋白形成中的重要性已被科学界所认识。然而，分离和量化特定的分子间相互作用如何影响或核化特定淀粉样蛋白聚集状态的形成一直是具有挑战性的。拟议中的研究将利用和扩展Matysiak博士实验室过去几年开发的计算模型，现在使Matysiak小组能够进行这种类型的研究。这项研究还将使研究生和本科生获得多尺度计算建模的专业培训。新的计算模型将被用于重新设计的计算建模课程，使用基于课程的本科生研究经验（CURE）approaches.This研究项目旨在表征糖胺聚糖（GAGs）的影响，肽膜相互作用和肽聚集的粗粒度和原子模型的使用。将在各种条件下研究几种淀粉样蛋白生成肽（功能性或毒性）的聚集。通过不同组成的混合双层和不同的特定多糖结构的存在下，将有助于马里兰州团队确定什么样的相互作用可以增强或抑制肽折叠/错误折叠和聚集。这项研究的信息预计将提供新的见解如何肽脂质，肽寡糖，寡糖脂质相互作用调整出现特定的淀粉样肽聚集形态和这些聚集过程的动力学。这个奖项反映了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。

With the support of the Chemistry of Life Processes (CLP) program in the Chemistry Division, Silvina Matysiak from the University of Maryland will investigate the molecular conditions that promote or impede amyloid formation in an environment mimicking the extracellular matrix. The extracellular matrix is a complex mesh of proteins and carbohydrates, and it is connected to the cells it surrounds, holding them together to form a tissue. Amyloids are proteinaceous deposits/aggregates. Amyloid formation is a critical factor in many normal biological processes and in neurodegenerative diseases, such as Alzheimer's disease. The importance of carbohydrates and the surface of cell membranes in modulating amyloid formation have been recognized by the scientific community. However, it has been challenging to isolate and quantify how specific intermolecular interactions influence or nucleate the formation of particular amyloid aggregation states. The proposed research will exploit and extend computational models, developed over the last few years in Dr. Matysiak’s lab, that now enable the Matysiak group to pursue this type of research. This research will also allow graduate and undergraduate students to acquire specialized training in multiscale computational modeling. The new computational models will be used in the redesigning of a computational modeling course using a course-based undergraduate research experience (CURE) approach.This research project seeks to characterize the effects of glycosaminoglycans (GAGs) in peptide-membrane interactions and peptide aggregation by the usage of coarse-grained and atomistic models. The aggregation of several amyloidogenic peptides (functional or toxic) will be studied under various conditions. Stepping through mixed bilayers of different compositions and in the presence of different specific polysaccharide structures will help the Maryland team to ascertain what interactions can enhance or suppress peptide folding/misfolding and aggregation. Information from this study is expected to provide new insight into how peptide-lipid, peptide-oligosaccharide, and oligosaccharide-lipid interactions tune the emergence of specific amyloid peptide aggregation morphologies and into the kinetics of these aggregation processes.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.