Deep profiling of protease substrate specificity enabled by dual random and scanned human proteome substrate phage libraries.
Deep profiling of protease substrate specificity enabled by dual random and scanned human proteome substrate phage libraries.
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通过双重随机和扫描的人类蛋白质组底物噬菌体库实现蛋白酶底物特异性的深度分析。
DOI：
10.1073/pnas.2009279117
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发表时间：
2020
影响因子：
11.1
通讯作者：
Wells,JamesA
中科院分区：
文献类型：
--
作者：
Zhou,Jie;Li,Shantao;Leung,KevinK;O'Donovan,Brian;Zou,JamesY;DeRisi,JosephL;Wells,JamesA
蛋白水解是细胞内外生物学的主要翻译后调节因子。广泛鉴定蛋白酶的最佳切割位点和天然底物对于药物发现和理解蛋白酶生物学至关重要。在这里，我们提出了一种方法，该方法采用两个遗传编码的底物噬菌体展示文库与下一代测序（SPD-NGS）相结合，与最先进的合成肽文库或蛋白质组学相比，该方法允许典型的6至8个残基蛋白酶切割位点的序列覆盖率高达10，000倍。我们将SPD-NGS应用于两类蛋白酶，细胞内半胱天冬酶和脱落酶的胞外域，亚当斯10和17。第一个文库（Lib 10AA）使我们能够在1,000倍的NGS计数动态范围内鉴定104至105个独特的切割位点，并产生基于位置特异性评分矩阵的一致性和最佳切割基序。第二个SPD-NGS文库（Lib hP），它显示了几乎整个人类蛋白质组平铺在连续的49个氨基酸序列与25个氨基酸重叠，使我们能够识别候选人的蛋白质组序列。我们确定了多达104个天然线性切割位点，这取决于蛋白酶，并捕获了以前通过蛋白质组学确定的大多数例子，并预测了10到100倍。结构生物信息学用于促进候选天然蛋白质底物的鉴定。SPD-NGS是快速的，可重复的，简单的执行和分析，廉价的，可再生的，具有前所未有的深度覆盖的底物序列，是一个重要的工具，蛋白酶生物学家感兴趣的蛋白酶特异性的特定测定和抑制剂，并促进天然蛋白质底物的鉴定。
Proteolysis is a major posttranslational regulator of biology inside and outside of cells. Broad identification of optimal cleavage sites and natural substrates of proteases is critical for drug discovery and to understand protease biology. Here, we present a method that employs two genetically encoded substrate phage display libraries coupled with next generation sequencing (SPD-NGS) that allows up to 10,000-fold deeper sequence coverage of the typical six- to eight-residue protease cleavage sites compared to state-of-the-art synthetic peptide libraries or proteomics. We applied SPD-NGS to two classes of proteases, the intracellular caspases, and the ectodomains of the sheddases, ADAMs 10 and 17. The first library (Lib 10AA) allowed us to identify 104to 105unique cleavage sites over a 1,000-fold dynamic range of NGS counts and produced consensus and optimal cleavage motifs based position-specific scoring matrices. A second SPD-NGS library (Lib hP), which displayed virtually the entire human proteome tiled in contiguous 49 amino acid sequences with 25 amino acid overlaps, enabled us to identify candidate human proteome sequences. We identified up to 104natural linear cut sites, depending on the protease, and captured most of the examples previously identified by proteomics and predicted 10- to 100-fold more. Structural bioinformatics was used to facilitate the identification of candidate natural protein substrates. SPD-NGS is rapid, reproducible, simple to perform and analyze, inexpensive, and renewable, with unprecedented depth of coverage for substrate sequences, and is an important tool for protease biologists interested in protease specificity for specific assays and inhibitors and to facilitate identification of natural protein substrates.