Infinite switch simulated tempering in force (FISST).

@article{Hartmann2020InfiniteSS,
  title={Infinite switch simulated tempering in force (FISST).},
  author={Michael J. Hartmann and Yuvraj Singh and Eric Vanden-Eijnden and Glen M. Hocky},
  journal={The Journal of chemical physics},
  year={2020},
  volume={152 24},
  pages={
          244120
        }
}
Many proteins in cells are capable of sensing and responding to piconewton-scale forces, a regime in which conformational changes are small but significant for biological processes. In order to efficiently and effectively sample the response of these proteins to small forces, enhanced sampling techniques will be required. In this work, we derive, implement, and evaluate an efficient method to simultaneously sample the result of applying any constant pulling force within a specified range to a… 

Figures from this paper

Assessing models of force-dependent unbinding rates via infrequent metadynamics.
TLDR
This work demonstrates the promise of predicting force-dependent unbinding rates using enhanced sampling MD techniques while also revealing the methodological barriers that must be overcome to tackle more complex targets in the future.
Recent Advances and Emerging Challenges in the Molecular Modeling of Mechanobiological Processes.
TLDR
The development of experimental techniques that can measure and characterize the tiny forces acting at the cellular scale and down to the single-molecule, biomolecular level has enabled access to unprecedented details about the involved mechanisms.
Size-and-Shape Space Gaussian Mixture Models for Structural Clustering of Molecular Dynamics Trajectories.
TLDR
This work presents a method, denoted shape-GMM, that overcomes the shortcomings of particle positions using a weighted maximum likelihood alignment procedure that is built into an expectation maximization Gaussian mixture model (GMM) procedure to capture metastable states in the free-energy landscape.
Molecular Paradigms for Biological Mechanosensing.
TLDR
The goal of this article is to provide a physical chemistry perspective on protein-based molecular mechanosensing paradigms used in living systems, and how these paradigm can be explored using novel computational methods.
Unified Approach to Enhanced Sampling
TLDR
This work introduces a new class of collective-variables-based bias potentials that can be used to sample any of the expanded ensembles normally sampled via replica exchange, and provides a practical implementation of the recently developed on-the-fly probability enhanced sampling method.

References

SHOWING 1-10 OF 66 REFERENCES
How Fast Is Too Fast in Force-Probe Molecular Dynamics Simulations?
TLDR
The parameters of this bias are quantified for the first time using a model system of four tandem spectrin repeats linked with long, flexible poly-glycine linkers and it is shown that for the fastest velocities, down to 1 m/s, the outer domains preferentially unfold.
GPR68 Senses Flow and Is Essential for Vascular Physiology
Rheology of Active Fluids
An active fluid denotes a viscous suspension of particles, cells, or macromolecules able to convert chemical energy into mechanical work by generating stresses on the microscale. By virtue of this
A Rheological Study of the Association and Dynamics of MUC5AC Gels.
TLDR
It is found that analyses of thermal fluctuations on the length scale of the micrometer-sized particles are not predictive of the linear viscoelastic response of the mucin gels, and that taken together, the results from both techniques help to provide complementary insight into the structure of the network.
Cell and molecular mechanics of biological materials
TLDR
The mechanical deformation of proteins and nucleic acids may provide key insights for understanding the changes in cellular structure, response and function under force, and offer new opportunities for the diagnosis and treatment of disease.
SciPy 1.0: fundamental algorithms for scientific computing in Python
TLDR
An overview of the capabilities and development practices of SciPy 1.0 is provided and some recent technical developments are highlighted.
Atomistic Simulations of Membrane Ion Channel Conduction, Gating, and Modulation.
TLDR
Modern simulations offer a range of molecular-level insights into ion channel function and modulation as a learning platform for mechanistic discovery and drug development.
Emerging Diversity in Lipid–Protein Interactions
TLDR
Overall, a complex picture of lipid–protein interactions emerges, through a range of mechanisms including modulation of the physical properties of the lipid environment, detailed chemical interactions between lipids and proteins, and key functional roles of very specific lipids binding to well-defined binding sites on proteins.
Mechanochemical Feedback Loops in Development and Disease
...
1
2
3
4
5
...