Single-molecule spectroscopy of amino acids and peptides by recognition tunnelling.
Single-molecule spectroscopy of amino acids and peptides by recognition tunnelling.
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DOI：
10.1038/nnano.2014.54
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发表时间：
2014-06
影响因子：
38.3
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中科院分区：
文献类型：
--
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由于RNA剪接和翻译后修饰，人类蛋白质组具有数百万种蛋白质变体，与疾病相关的变体通常以微小浓度存在。对于DNA和RNA，可以使用聚合酶链反应扩增低浓度，但对于蛋白质没有这样的反应。因此，单分子蛋白质测序的发展是寻找蛋白质生物标志物的关键步骤。在这里，我们表明，可以通过捕获分子之间的两个电极，涂有一层识别分子和测量电子隧道电流通过结识别单个氨基酸。一个给定的分子可以在连接处以多种方式结合，因此我们使用机器学习算法来区分与每个结合基序相关的电子“指纹”集。利用这种识别隧道技术，我们能够识别D，L对映体，甲基化氨基酸，同量异位异构体和短肽。结果表明，通过依次测量进行性外肽酶消化的产物，或通过使用分子马达将蛋白质拉过与纳米孔集成的隧道结，可以对单个蛋白质进行直接电子测序。
The human proteome has millions of protein variants due to alternative RNA splicing and post-translational modifications, and variants that are related to diseases are frequently present in minute concentrations. For DNA and RNA, low concentrations can be amplified using the polymerase chain reaction, but there is no such reaction for proteins. Therefore, the development of single molecule protein sequencing is a critical step in the search for protein biomarkers. Here we show that single amino acids can be identified by trapping the molecules between two electrodes that are coated with a layer of recognition molecules and measuring the electron tunneling current across the junction. A given molecule can bind in more than one way in the junction, and we therefore use a machine-learning algorithm to distinguish between the sets of electronic ‘fingerprints’ associated with each binding motif. With this recognition tunneling technique, we are able to identify D, L enantiomers, a methylated amino acid, isobaric isomers, and short peptides. The results suggest that direct electronic sequencing of single proteins could be possible by sequentially measuring the products of processive exopeptidase digestion, or by using a molecular motor to pull proteins through a tunnel junction integrated with a nanopore.
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影响因子：
3.7
作者：
Huang, Shuo;Chang, Shuai;He, Jin;Zhang, Peiming;Liang, Feng;Tuchband, Michael;Li, Shengqing;Lindsay, Stuart
通讯作者：
Lindsay, Stuart
影响因子：
4.3
作者：
Liang, Feng;Li, Shengqing;Lindsay, Stuart;Zhang, Peiming
通讯作者：
Zhang, Peiming
影响因子：
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作者：
Lindsay S;He J;Sankey O;Hapala P;Jelinek P;Zhang P;Chang S;Huang S
通讯作者：
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影响因子：
64.8
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通讯作者：
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影响因子：
38.3
作者：
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通讯作者：
Kawai, Tomoji