Systems Pharmacology Model for Spatial Control of Cardiac Fibrosis

大多数最初在心肌梗死中幸存下来的人后来都面临着生命危险。 并发症，如梗塞破裂、心律失常或心力衰竭。这些后遗症严重依赖于伤口 梗塞的愈合和远端心肌的纤维化，然而现有的药物并不是设计用来 专门针对这两个目标之一。一种理想的药物治疗将增强血管内皮细胞的细胞外基质 在减少远端心肌纤维化的同时减少梗塞，但实现了对细胞外的这种空间控制 黑客帝国躲过了这一领域。我们提出，对全球应用的药物的这些不同的局部反应可以是 通过利用与环境相关的信号机制实现，该机制与系统唯一标识 药理学模型。我们首次将药物-靶向相互作用数据库与一种新的大规模 心脏信号网络模型，用于识别引起上下文相关调节的药物或药物对 细胞外基质与培养的心脏成纤维细胞的结合。然后，我们将信令网络模型与 炎症和心肌梗死愈合的药剂模型。将该集成模型应用于 执行多尺度虚拟药物筛选以预测并在实验中验证可增强 在减少远隔心肌纤维化的同时，减少梗死灶中的细胞外基质。总体而言，这项研究将 为心脏纤维化的多尺度系统药理学提供创新框架，确定新的 梗塞愈合的治疗方法，并为药物反应的空间控制提供概念验证 通过利用上下文相关的小区信令。

The majority of individuals that initially survive a myocardial infarction go on to suffer from life-threatening complications such as infarct rupture, arrhythmia, or heart failure. These sequelae depend critically on wound healing in the infarct as well as fibrosis in the remote myocardium, yet existing drugs are not designed to specifically target either of these. An ideal pharmacologic therapy would enhance extracellular matrix in the infarct while reducing fibrosis in the remote myocardium, but achieving such spatial control of extracellular matrix has eluded the field. We propose that these distinct local responses to globally applied drugs can be achieved by leveraging environment-dependent signaling mechanisms, uniquely identified with systems pharmacology models. We first integrate drug-target interaction databases together with a novel large-scale model of the cardiac signaling network to identify drugs or drug pairs that cause context-dependent regulation of extracellular matrix with cultured cardiac fibroblasts. We then integrate the signaling network model with agent-based models of inflammation and myocardial infarct healing. This integrated model is applied to perform multi-scale virtual drug screening to predict and then experimentally validate drugs that enhance extracellular matrix in the infarct while reducing fibrosis in the remote myocardium. Overall, this study will provide an innovative framework for multi-scale systems pharmacology of cardiac fibrosis, identify new therapeutic approaches for infarct healing, and provide proof-of-concept for spatial control of drug responses by leveraging context-dependent cell signaling.