Single‐Molecule Classification of Aspartic Acid and Leucine by Molecular Recognition through Hydrogen Bonding and Time‐Series Analysis
Single‐Molecule Classification of Aspartic Acid and Leucine by Molecular Recognition through Hydrogen Bonding and Time‐Series Analysis
复制标题
通过氢键分子识别和时间序列分析对天冬氨酸和亮氨酸进行单分子分类
DOI：
10.1002/asia.202200179
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Taniguchi Masateru
中科院分区：
文献类型：
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作者：
Ryu Jiho;Komoto Yuki;Ohshiro Takahito;Taniguchi Masateru
氨基酸检测/鉴定方法对于理解生物系统是重要的。在这项研究中，我们开发了单分子测量来研究化学修饰的量子隧穿增强，并进行了基于机器学习的时间序列分析来开发准确的氨基酸识别。我们用巯基乙酸（MAA）化学修饰的纳米间隙对L-天冬氨酸（Asp）和L-亮氨酸（Leu）进行了单分子测量。通过基于机器学习的时间序列分析方法研究测量的电流，以进行准确的氨基酸区分。与使用裸纳米间隙的测量相比，发现MAA改性通过氢键促进隧穿现象改善了Asp和Leu之间的电导-时间曲线的差异。还发现该方法能够测定相对浓度。即使在天冬氨酸和亮氨酸的混合物中。它改善了氨基酸的选择性分析，因此将适用于医学，诊断和单分子肽测序。
Amino acid detection/identification methods are important for understanding biological systems. In this study, we developed single‐molecule measurements for investigating quantum tunneling enhancement by chemical modification and carried out machine learning‐based time series analysis for developing accurate amino acid discrimination. We performed single‐molecule measurement of L‐aspartic acid (Asp) and L‐leucine (Leu) with a mercaptoacetic acid (MAA) chemical modified nano‐gap. The measured current was investigated by a machine learning‐based time series analysis method for accurate amino acid discrimination. Compared to measurements using a bare nano‐gap, it is found that MAA modification improves the difference in the conductance‐time profiles between Asp and Leu through the hydrogen bonding facilitated tunneling phenomena. It is also found that this method enables determination of relative concentration. even in the mixture of Asp and Leu. It improves selective analysis for amino acids and therefore would be applicable in medicine, diagnosis, and single‐molecule peptide sequencing.