Computational models for the signaling of tumor necrosis factor receptor on cell surfaces

项目概要 先天免疫系统构成宿主防御的第一道防线。外来入侵 病原体会导致炎症反应，包括肿胀等临床症状。 在炎症过程中，受损细胞会释放细胞因子。  他们招募白细胞 到达受伤部位并清除外来病原体。超家族中的蛋白质 肿瘤坏死因子（TNF）是这些细胞因子中的一类主要细胞因子。它们与细胞结合 称为 TNF 受体的表面蛋白。 TNF 与受体的结合会触发 细胞内信号通路，如 NF-κB 通路，是细胞的重要调节因子 生存。由于这种在免疫反应中的关键作用，TNF 受体与其结合 配体正在深入研究中。然而，大多数这些研究分离了 TNF 受体 来自他们通常的生物环境。在活细胞中，TNF 受体锚定于 质膜表面。 TNF 受体的膜限制导致 对其功能产生重大影响。例如，TNF配体寡聚化提供 与受体的高局部结合亲和力。此外，TNF受体可以聚集成高 配体结合后排列簇。这些现象背后的机制并不完全 由于当前实验的限制而被理解。计算建模可以达到 目前实验室无法达到的尺寸。因此，本次活动的目的 建议是分解 TNF 可溶性配体之间结合动力学的复杂性 和细胞表面结合受体。我们开发了不同的计算方法 蛋白质之间的结合亲和力并模拟蛋白质结合动力学 分子和较低分辨率水平。通过应用这些方法 TNF 受体结合在细胞表面的具体问题，以及建立持续的 实验合作，我们特别有兴趣回答以下两个问题 问题：TNF配体的寡聚化如何调节受体结合，以及 TNF 受体簇在调节配体结合中的功能作用是什么。在 为了研究这两个问题，我们构建了一个新的基于领域的刚体模型 并进一步开发多尺度建模框架来定量计算 多价配体与细胞表面多个受体之间的结合动力学。 我们的长期目标是进一步阐明 TNF 介导的信号传导在 调节炎症反应。总而言之，本研究将阐明基本的 TNF 受体结合细胞表面的机制。

Project Summary The innate immune system constitutes the first line of host defense. The invasion of external pathogens leads into inflammatory responses, including the clinical signs such as swelling. During inflammation, cytokines are released from injured cells.  They recruit leukocytes to reach the site of injury and remove the foreign pathogens. Proteins in the superfamily of tumor necrosis factor (TNF) are one major class of these cytokines. They bind to the cell surface proteins called TNF-receptors. The binding between TNF and receptors triggers the intracellular signaling pathways, such as NF-κB pathway that is an essential regulator of cell survival. Due to this critical role in immune responses, binding of TNF receptors with their ligands is under intense study. However, most of these studies isolate the TNF receptors from their usual biological surrounding. In living cells, TNF receptors are anchored on surfaces of plasma membrane. The membrane confinement of TNF receptors causes significant impacts on their functions. For instance, the TNF ligand oligomerization provides high local binding avidity to receptors. Moreover, TNF receptors can aggregate into high- order clusters upon ligand binding. Mechanisms underlying these phenomena are not fully understood due to current experimental limitations. Computational modeling can reach dimensions that are currently unapproachable in the laboratory. Thus, the objective of this proposal is to decompose the complexity of binding kinetics between TNF soluble ligands and cell-surface-bound receptors. We have developed different methods for calculating binding affinities between protein and simulating protein binding kinetics on the molecular and lower-resolution levels. Through the application of these methods to the specific problem of TNF receptor binding on cell surfaces, and the establishment of ongoing experimental collaborations, we are specifically interested in answering the following two questions: how does oligomerization of TNF ligands modulate receptor binding, and what are the functional roles of TNF receptor clustering in regulating ligand binding. In order to study these two problems, we construct a new domain-based rigid-body model and further develop a multiscale modeling framework to quantitatively calculate the kinetics of binding between multivalent ligands and multiple receptors on cell surfaces. Our long-term goal is to further elucidate the functional roles of TNF-mediated signaling in regulating the inflammatory responses. In summary, this study will shed light on the basic mechanisms of TNF receptor binding on cell surface.