Real-time identification of multiple nanoclusters with a protein nanopore in single-cluster level
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It is important and challenging to analyze nanocluster structure with atomic precision. Herein, α-hemolysin nanopore was used to identify nanoclusters at the single molecule level by providing two-dimensional (2D) dwell time–current blockage spectra and translocation event frequency which sensitively depended on their structures. Nanoclusters such as Anderson, Keggin, Dawson, and a few lacunary Dawson polyoxometalates with very similar structures, even with only a two-atom difference, could be discriminated. This nanopore device could simultaneously measure multiple nanoclusters in a mixture qualitatively and quantitatively. Furthermore, molecular dynamics (MD) simulations provided microscopic understandings of the nanocluster translocation dynamics and yielded 2D dwell time–current blockage spectra in close agreement with experiments. The nanopore platform provides a novel powerful tool for nanocluster characterization.
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Real-time identification of multiple nanoclusters with a protein nanopore in single-cluster level
Abstract
It is important and challenging to analyze nanocluster structure with atomic precision. Herein, α-hemolysin nanopore was used to identify nanoclusters at the single molecule level by providing two-dimensional (2D) dwell time–current blockage spectra and translocation event frequency which sensitively depended on their structures. Nanoclusters such as Anderson, Keggin, Dawson, and a few lacunary Dawson polyoxometalates with very similar structures, even with only a two-atom difference, could be discriminated. This nanopore device could simultaneously measure multiple nanoclusters in a mixture qualitatively and quantitatively. Furthermore, molecular dynamics (MD) simulations provided microscopic understandings of the nanocluster translocation dynamics and yielded 2D dwell time–current blockage spectra in close agreement with experiments. The nanopore platform provides a novel powerful tool for nanocluster characterization.
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Acknowledgements
This work was financially supported by the National Key Research and Development Program of China (No. 2021YFA1200104), New Cornerstone Science Foundation, the National Natural Science Foundation of China (Nos. 22027807, 22034004, and 22078104), the Strategic Priority Research Program of Chinese Academy of Sciences (No. XDB36000000), and Tsinghua-Vanke Special Fund for Public Health and Health Discipline Development (No. 2022Z82WKJ003). CPU hours allocated by the Guangzhou Supercomputer Center of China are gratefully acknowledged.
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