Proteolytic Activity Matrix Analysis (PrAMA) for simultaneous determination of multiple protease activities.
Proteolytic Activity Matrix Analysis (PrAMA) for simultaneous determination of multiple protease activities.
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用于同时测定多种蛋白酶活性的蛋白水解活性基质分析（PRAMA）。
DOI：
10.1039/c0ib00083c
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发表时间：
2011-04
期刊：
影响因子：
--
通讯作者：
Lauffenburger DA
中科院分区：
文献类型：
--
作者：
Miller MA;Barkal L;Jeng K;Herrlich A;Moss M;Griffith LG;Lauffenburger DA
基质金属蛋白酶（Matrix metalloproteinases, MMPs）和A - Disintegrin and metalloproteinases （ADAMs）是两个相关的蛋白酶家族，在基质重塑和生长因子配体脱落中起关键作用。以无创、实时、多重的方式直接确定生理环境中特定MMPs和ADAMs的蛋白水解活性仍然是一个挑战。这项工作描述了蛋白水解活性矩阵分析（PrAMA），这是一种集成的实验测量和数学分析框架，可同时确定MMPs和ADAMs复杂混合物中特定酶的活性。PrAMA方法解释来自中等特异性的基于fret的多肽蛋白酶底物的动态信号，以推断特定的MMP和ADAM蛋白水解活性的概况。使用纯化酶测量的底物面板的单个MMP/ADAM切割特征的先验数据来完成复杂蛋白酶混合物信号的反褶积。我们首先使用大约4000个涉及已知纯化酶和底物混合物的测量资料来验证PrAMA推断，然后演示应用于野生型、ADAM10−/−和ADAM17−/−成纤维细胞对磷酸酯刺激的活细胞反应。结果表明，即使存在未知的背景蛋白水解活性，PrAMA也能以较高的准确度区分密切相关的酶。PrAMA提供了一个有价值的工具，应用范围从活细胞体外检测到复杂酶混合物的高通量抑制剂筛选。此外，我们的方法可以扩展到其他蛋白酶家族，如半胱天冬酶和组织蛋白酶，它们也可能缺乏高度特异性的底物。
Matrix metalloproteinases (MMPs) and A Disintegrin and Metalloproteinases (ADAMs) are two related protease families that play key roles in matrix remodeling and growth factor ligand shedding. Directly ascertaining the proteolytic activities of particular MMPs and ADAMs in physiological environments in a non-invasive, real-time, multiplex manner remains a challenge. This work describes Proteolytic Activity Matrix Analysis (PrAMA), an integrated experimental measurement and mathematical analysis framework for simultaneously determining the activities of particular enzymes in complex mixtures of MMPs and ADAMs. The PrAMA method interprets dynamic signals from panels of moderately specific FRET-based polypeptide protease substrates to deduce a profile of specific MMP and ADAM proteolytic activities. Deconvolution of signals from complex mixtures of proteases is accomplished using prior data on individual MMP/ADAM cleavage signatures for the substrate panel measured with purified enzymes. We first validate PrAMA inference using a compendium of roughly 4000 measurements involving known mixtures of purified enzymes and substrates, and then demonstrate application to the live-cell response of wildtype, ADAM10−/−, and ADAM17−/− fibroblasts to phorbol ester stimulation. Results indicate PrAMA can distinguish closely related enzymes from each other with high accuracy, even in the presence of unknown background proteolytic activity. PrAMA offers a valuable tool for applications ranging from live-cell in vitro assays to high-throughput inhibitor screening with complex enzyme mixtures. Moreover, our approach may extend to other families of proteases, such as caspases and cathepsins, that also can lack highly-specific substrates.
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