BSML:用于多组分和多目标分析的生物协同建模语言

W. Hwang, Jaejoon Choi, J. Jung, Doheon Lee
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引用次数: 3

摘要

多种复合药物被认为是克服药物疗效有限和脱靶效应的最有希望的解决方案。然而,通过实验测试确定有希望的多种化合物需要巨大的成本和大量的测试。基于系统生物学的方法被认为是最有前途的策略之一。预测药物在生物系统中的反应是系统生物学的目标之一。生物协同建模语言(BSML)是一种多尺度的生物系统建模语言。BSML包含涵盖空间尺度、时间尺度和状况信息(如疾病)的上下文信息。我们将BSML应用于2型糖尿病(T2D)模型,该模型涉及胰腺、肝脏、肌肉等多个器官的功能障碍。我们从公共数据库中自动提取了12522条t2d相关规则。采用Petri网模拟单药和联合用药在T2D模型上的反应。我们的模拟结果显示了候选T2D药物以及联合药物如何在全身范围内起作用。我们期望我们的工作将为在全身范围内识别有前途的联合药物和联合药物的机制提供见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BSML: bio-synergy modeling language for multi-component and multi-target analysis
Multi-compound drugs are considered as the most promising solution to overcome the limited efficacy and off-target effect of drugs. However, identifying promising multiple compounds by experimental tests requires overwhelming costs and a number of tests. Systems biology-based approaches are regarded as one of the most promising strategy. To predict responses of drugs in biological systems is one of aims of Systems biology. We made Bio-Synergy Modeling Language (BSML) for modeling biological systems, which are multi-scale systems. BSML contains context information that covers spatial scales, temporal scales, and condition information, such as disease. We have applied BSML to generate type 2 diabetes (T2D) model, which involves malfunctions of numerous organs such as pancreas, liver, and muscle. We have extracted 12,522 T2D-related rules from public databases automatically. We simulated responses of single drugs and combination drugs on the T2D model by Petri nets. The results of our simulation show candidate T2D drugs and how combination drugs could act on whole-body scales. We expect that our work would provide an insight for identifying promising combination drugs and mechanisms of combination drugs on whole body scales.
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