Journal of Chemical Theory and ComputationBiophysicsPeer-reviewed journal article
Multiscale Responsive Kinetic Modeling: Quantifying Biomolecular Reaction Flux under Varying Electrochemical Conditions
Hannah Weckel-DahmaniD, Ryan CarlseniD, Jessica M. J. SwansoniD
Abstract
Attaining a complete thermodynamic and kinetic characterization for processes involving multiple interconnected rare-event transitions remains a central challenge in molecular biophysics. This challenge is amplified when the process must be understood under a range of reaction conditions. Herein, we present a condition-responsive kinetic modeling framework that can combine the strengths of bottom-up rate quantification from multiscale simulations with top-down solution refinement using experimental data. Although this framework can be applied to any process, we demonstrate its use for electrochemically driven transport through channels and transporters. Using the Cl- /H+ antiporter ClC-ec1 as a model system, we show how robust and predictive kinetic solutions can be obtained when the solution space is grounded by thermodynamic constraints, seeded through multiscale rate quantification, and further refined with experimental data, such as electrophysiology assays. Turning to the Shaker K+ channel, we demonstrate that robust solutions and biophysical insights can also be obtained with sufficient experimental data. This multi-pathway method proves capable of identifying single-pathway dominant mechanisms but also highlights that competing and off-pathway flux is still essential to replicate experimental findings and to describe concentration-dependent channel rectification.
- assay: electrophysiology
- research focus: protein folding & dynamics
- approach: deep learning
- approach: statistical model
- Citations
- 5
- FWCI
- 0.58
- Field percentile
- top 40%
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