Tissue Selective Glucocorticoids

应激激素皮质醇，协调身体的慢性代谢，但也协调对应激的急性反应， 调节不同组织中的干细胞分化，抑制炎症和免疫反应， 过度活跃，并协调对营养成分和进食或禁食的急性代谢反应。皮质醇也是 被称为糖皮质激素，因为它控制葡萄糖代谢。合成糖皮质激素（GC）广泛用于 它可以减少许多疾病的疼痛和炎症，但会导致胰岛素抵抗、肌肉萎缩和骨质疏松症。 我们已经开发了一种研究GC的方法，使我们能够了解糖皮质激素受体如何协调 通过与特定基因结合并改变这些基因产生的蛋白质来控制组织选择性 活动这是因为GC与受体结合并改变其形状，使其能够与不同的酶相互作用， 控制转录。以前理解这些过程的努力受到了阻碍，因为大多数现有的 我们研究的GC非常相似。相反，我们使GC具有全方位的可取和不可取的活动， 这给了我们统计学上的差异来理解它们，我们称之为配体类别分析的技术， 与不同的转录调节酶相互作用以控制特定基因表达的GC配体类别。 另一个主要障碍是需要非常广泛的专业知识来理解GC化学结构之间的联系， 受体结构、相互作用的辅助调节因子、调节基因和组织选择活性。我们已经组建 所需的专业知识和方法，以克服这些障碍，通过研究GC对骨骼肌，干细胞， 分化成骨、炎症和对结肠炎的免疫反应。我们将使用化学系统生物学方法 与新型GC沿着与整合结构生物学平台一起定义糖皮质激素的信号传导密码 目标1生物学：确定哪些GC效应是相关的，哪些可以用 用于骨骼肌、T细胞分化、炎症和结肠炎研究的生理学相关生物学，以及 成骨细胞矿化和对骨的影响。目标2化学：开发GC以干扰GR结构和功能 以新颖的方式。我们将根据具体的结构假设扩大三类化合物，以扩大化学- 结构空间和测试一种新的甾体支架以进入新的化学空间。化学将专注于创造一种多样性 在保持化合物的抗炎作用的同时，对骨与骨骼肌的作用。目标3结构： 确定选择性GC信号传导的结构基础。我们将应用机器学习和回归方法 我们的结构和生物学数据，以建立和测试模型，定义驱动组织选择性的机制， 这些过程是全局协调的，以在生物体水平上控制分化和应激反应。 理解选择性调制的结构和分子机制将导致突破性的理解 以及改进气相色谱的发展。

The stress hormone, cortisol, coordinates the body’s chronic metabolism, but also coordinates acute responses to stress by regulating stem cell differentiation in different tissues, restraining inflammatory and immune responses from being hyperactive, and coordinates acute metabolic responses to nutrient composition and feeding or fasting. Cortisol is also known as a glucocorticoid because it controls glucose metabolism. Synthetic glucocorticoids (GCs) are wide used for reducing pain and inflammation across many diseases, but can cause insulin resistance, muscle atrophy, and osteoporosis. We have developed an approach to studying GCs that enables us to understand how the glucocorticoid receptor coordinates these activities by binding to specific genes and changing the proteins made by those genes to control tissue-selective activity. This occurs as the GCs bind to the receptor and change its shape, enabling it to interact with different enzymes that control transcription. Previous efforts to understand these processes have been hampered by the fact that most of the existing GCs that we study are very similar. We instead make GCs that have a full range of desirable and undesirable activities, which gives us the statistical variance to understand them, a technique we call ligand class analysis, as we identify different classes of GC ligands that interact with different transcriptional regulatory enzymes to control expression of specific genes. Another major barrier has been the very wide expertise needed to understand the links between the GC chemical structure, receptor structure, the interacting coregulators, the regulated genes, and the tissue selective activities. We have assembled the required expertise and approaches to overcome these barriers by studying GC action on skeletal muscle, stem cell differentiation into bone, inflammation, and immune responses to colitis. We will use a chemical systems biology approach with novel GCs along with an integrative structural biology platform to define the signaling code for the glucocorticoid receptor in these aims: Aim 1 Biology: Identify which GC effects are correlated and which can be separated using physiologically relevant biology for the study of skeletal muscle, T cell differentiation, inflammation, and colitis, and osteoblast mineralization and effects on bone. Aim 2 Chemistry: Development of GCs to perturb GR structure and function in novel ways. We will enlarge three classes of compounds based on specific structural hypotheses to enlarge the chemical- structural space and test a novel steroidal scaffold to access new chemical space. Chemistry will focus on creating a diversity of effects on bone versus skeletal muscle while maintaining anti-inflammatory effects of the compounds. Aim 3 Structure: identify the structural underpinnings of selective GC signaling. We will apply machine learning and regression approaches to our structural and biological data to build and test models defining the mechanisms drive tissue-selectivity and identify which processes are globally coordinated to control differentiation and stress responses at an organismal level. Understanding the structural and molecular mechanisms of selective modulation will lead to breakthrough understandings of allostery and the development of improved GCs for medicine.