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Updated: Jun 13, 2026

Microfluidic Mixers for Studying Protein Folding
Published on: April 10, 2012
Complete all-atom hydrodynamics of protein unfolding in uniform flow
Guan M Wang1, William C Sandberg
1Department of Bioinformatics and Computational Biology, George Mason University, Manassas, VA, USA. guan1@sigmaxi.net
Abstract:
The unfolding dynamics of a protein, ubiquitin, pinned in several uniform flows, was studied at low and high flow rates in an all-atom style through a non-equilibrium molecular dynamics approach with explicit water molecules included. Atomic hydrodynamic force components on individual amino acids, as a function of time, due to the collisional interactions with the flowing water molecules were calculated explicitly. The protein conformational change in response to those time-varying forces was computed completely at the high flow rate up to nanosecond until the fully stretched state was reached. The end-to-end length of the single ubiquitin protein molecule at high flow rate is smoothly increasing. The step-like jumps between metastable states that describe the microm ms(-1) scale force pulling experiments conducted on polyubiquitins at low flow rates, are not seen at the high flow speeds necessary to computationally probe the ns nm(-1) scale regime. No unfolding was observed in the low flow rate atomic computations at nanosecond scale while partial and complete unfolding was observed in the coarse-grained low flow rate computations at microsecond scale. Examination of the all-atom computation of the time variation of the hydrodynamic forces on, and the velocity components of, the protein molecule unveiled to some extent the details of the complexity of the hydrodynamic friction variation in the nm ns(-1) regime of high rate flow-driven protein unfolding. This demonstrates quantitatively that all-atom computations are more suitable than the Langevin equation or Brownian dynamics methods for probing the interaction dynamics and resulting conformational dynamics of protein unfolding in strong flows on nm ns(-1) time/length scales while the reverse is true for investigation of slow, diffusively driven systems.
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