Protein Transport through Nanopores Illuminated by Long-Time-Scale Simulations
Source abstract
Abstract
The transport of molecules through nanoscale confined space is relevant in biology, biosensing, and industrial filtration. Microscopically modeling transport through nanopores is required for a fundamental understanding and guiding engineering, but the short duration and low replica number of existing simulation approaches limit statistically relevant insight. Here we explore protein transport in nanopores with a high-throughput computational method that realistically simulates hundreds of up to seconds-long protein trajectories by combining Brownian dynamics and continuum simulation and integrating both driving forces of electroosmosis and electrophoresis. Ionic current traces are computed to enable experimental comparison. By examining three biological and synthetic nanopores, our study answers questions about the kinetics and mechanism of protein transport and additionally reveals insight that is inaccessible from experiments yet relevant for pore design. The discovery of extremely frequent unhindered passage can guide the improvement of biosensor pores to enhance desired biomolecular recognition by pore-tethered receptors. Similarly, experimentally invisible nontarget adsorption to pore walls highlights how to improve recently developed DNA nanopores. Our work can be expanded to pressure-driven flow to model industrial nanofiltration processes.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Nanopore and Nanochannel Transport Studies · Electrostatics and Colloid Interactions · Membrane Separation Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Analysis and Scientific Computing, TU Wien, Vienna, 1040, Austria
Department of Chemistry, Institute of Structural Molecular Biology, University College London, London, WC1E 6BT, United Kingdom
Institute of Biophysics, Johannes Kepler University Linz, Linz, 4020, Austria
School of Mathematical and Statistical Sciences, Arizona State University, Tempe, Arizona 85287, United States
Funding
Austrian Science Fund
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