State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, 163 Xianlin Road, 210023, Nanjing, P. R. China.
Chemistry and Biomedicine Innovation Center, Nanjing University, 163 Xianlin Road, 210023, Nanjing, P. R. China.
Angew Chem Int Ed Engl. 2021 Nov 8;60(46):24582-24587. doi: 10.1002/anie.202108226. Epub 2021 Sep 6.
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 reveals the dissociation rate between nanopore and ions; the peak amplitude a 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.
生物纳米孔中分子和离子的传输受受限离子、传输分子和孔内壁残基之间相互作用网络的控制。然而，由于电化学测量的限制，要从纳米孔内仅数十个离子中识别出这种微弱的离子波动是很困难的。在这里，我们开发了一种先进的频率方法，可以对纳米孔内的离子相互作用网络进行定性和光谱分析。峰值频率 f 揭示了纳米孔与离子之间的离解速率；峰值幅度 a 描述了相互作用平衡后与纳米孔结合的离子数量。用于单分子频率指纹的数学模型实现了对突变纳米孔相互作用特性的预测。这种单分子频率指纹对于纳米限制内协同相互作用网络的分类、表征和预测非常重要。
