详细信息
Single-Molecule Frequency Fingerprint for Ion Interaction Networks in a Confined Nanopore ( SCI-EXPANDED收录 EI收录)
文献类型:期刊文献
英文题名:Single-Molecule Frequency Fingerprint for Ion Interaction Networks in a Confined Nanopore
作者:Li, Xinyi[1];Ying, Yi-Lun[1,2];Fu, Xi-Xin[3];Wan, Yong-Jing[3];Long, Yi-Tao[1]
机构:[1]Nanjing Univ, Sch Chem & Chem Engn, State Key Lab Analyt Chem Life Sci, 163 Xianlin Rd, Nanjing 210023, Peoples R China;[2]Nanjing Univ, Chem & Biomed Innovat Ctr, 163 Xianlin Rd, Nanjing 210023, Peoples R China;[3]East China Univ Sci & Technol, Sch Informat Sci & Engn, 130 Meilong Rd, Shanghai 200237, Peoples R China
年份:2021
卷号:60
期号:46
起止页码:24582
外文期刊名:ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
收录:;EI(收录号:20213610869274);WOS:【SCI-EXPANDED(收录号:WOS:000693803100001)】;
基金:This work was supported by the National Natural Science Foundation of China (21922405, 22027806 and 2209005). Y.-L.Y. is sponsored by National Ten Thousand Talent Program for young top-notch talent. We would like to thank Dr. Meng-Yin Li, Dr. Xue-Yuan Wu, and Dr. Shao-Chuang Liu for their fruitful discussion and help of protein engineering.
语种:英文
外文关键词:ion interaction networks; nanoelectrochemistry; nanopore; single-molecule analysis
摘要:The transport of molecules and ions through biological nanopores is governed by interaction networks among restricted ions, transported molecules, and residue moieties at pore inner walls. However, identification of such weak ion fluctuations from only few tens of ions inside nanopore is hard to achieve owing to electrochemical measurement limitations. Here, we developed an advanced frequency method to achieve qualitative and spectral analysis of ion interaction networks inside a nanopore. The peak frequency f(m) reveals the dissociation rate between nanopore and ions; the peak amplitude a(m) depicts the amount of combined ions with the nanopore after interaction equilibrium. A mathematical model for single-molecule frequency fingerprint achieved the prediction of interaction characteristics of mutant nanopores. This single-molecule frequency fingerprint is important for classification, characterization, and prediction of synergetic interaction networks inside nanoconfinement.
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