Using phosphorylation signatures of drug perturbagens to identify exercise-mimetic compounds

项目摘要 蛋白质磷酸化在微扰诱导的信号转导中起主要作用。综合图书馆 基于网络的签名（LINCS）P100项目已经产生了针对性的（使用96精心挑选的 磷酸盐）和综合（使用DIA，数据独立采集）质谱（MS）为基础的 磷酸化蛋白质组学数据集表征使用一组常见的生物活性 治疗（“已知”）化合物。使用DIA获得的磷酸化蛋白质组学数据的分析是具有挑战性的， 因此，全面的LINCS DIA数据尚未充分发挥其潜力。分子 身体活动传感器（MoTrPAC）联盟也使用磷酸蛋白质组学（沿着其他 组学数据）来量化运动的分子效应。使用翻译后修饰位点等方法- 特异性富集分析（PTM-SEA，Krug et al. MCP，2019），扰动诱导磷酸化 标记可以与运动诱导的磷酸化变化相关联，以鉴定已知的化合物， 可以模仿身体活动的效果，提供了一个令人兴奋的机会，以提高综合效用， LINCS和MoTrPAC共同基金数据集的影响。 我们的建议的目标是测试假设，有已知的化合物，可以模仿的影响， 体力活动。为了实现这一目标，PTM签名数据库（PTMsigDB）将大大提高 使用LINCS DIA数据扩展。然后将这些签名与磷酸化蛋白质组学变化相关联 由MoTrPAC提供的身体活动诱导，以提名运动模拟药物。 考虑到这些目标，我们将1）开发和应用基于云的自动化管道， 从现有的LINCS数据从100到几千个不同的磷酸化位点的磷酸化扰动概况; 2） 从大大扩展的磷酸化分析数据中推导出扰动特异性磷酸化蛋白质组学特征; 和3）使用MoTrPAC磷酸化蛋白质组学数据中的PTM标记富集来鉴定运动模拟药物 急性和长期运动。成功实施拟议战略将提名一份名单， 运动模拟药物有可能启动全新的研究途径，重点是寻找新的 对抗癌症患者的衰老或肌肉萎缩（恶病质）的治疗方法。

Project Summary Protein phosphorylation plays a major role in perturbation-induced signal transduction. The Library of Integrated Network-based Signatures (LINCS) P100 project has generated targeted (using 96 carefully chosen phosphosites) and comprehensive (using DIA, data independent acquisition) mass spectrometry (MS)-based phosphoproteomic datasets characterizing cell states perturbed using a collection of common bioactive therapeutic (“known”) compounds. The analysis of phosphoproteomics data acquired using DIA is challenging, and as a result the comprehensive LINCS DIA data has not yet been leveraged to its full potential. The Molecular Transducers of Physical Activity (MoTrPAC) consortium has also used phosphoproteomics (along with other omics data) to quantify the molecular effects of exercise. Using methods like post-translational modification site- specific enrichment analysis (PTM-SEA, Krug et al. MCP, 2019), perturbation-induced phosphorylation signatures can be correlated with exercise-induced phosphorylation changes to identify known compounds that can mimic the effects of physical activity, providing an exciting opportunity to enhance the combined utility and impact of the LINCS and MoTrPAC Common Fund datasets. The goal of our proposal is to test the hypothesis that there are known compounds that can mimic the effects of physical activity. To accomplish this goal, the PTM signatures database (PTMsigDB) will be significantly expanded using the LINCS DIA data.These signatures will then be correlated with phosphoproteomic changes induced by physical activity provided by MoTrPAC to nominate exercise-mimetic drugs. With these goals in mind we will 1) Develop and apply an automated, cloud-based pipeline to greatly expand phospho-perturbation profiles from existing LINCS data from 100 to several thousand distinct phosphosites; 2) Derive perturbation-specific phosphoproteomic signatures from the greatly expanded phospho-profiling data; and 3) Identify exercise mimetic drugs using PTM signature enrichment in MoTrPAC phosphoproteomic data from acute and long-term exercise. Successful application of the proposed strategy will nominate a list of exercise-mimetic drugs with the potential to initiate entirely new avenues of research focused on finding new therapeutic approaches to combat aging or muscle wasting (cachexia) in cancer patients.