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Updated: May 31, 2025

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Published on: March 1, 2022

Entropy-based methods for formulating bottom-up ultra-coarse-grained models.

Patrick G Sahrmann¹, Gregory A Voth¹

¹Department of Chemistry, Chicago Center for Theoretical Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois 60637, USA.

The Journal of Chemical Physics

|January 22, 2025

Summary

This summary is machine-generated.

Ultra Coarse-Graining (UCG) modeling enhances simulations by incorporating many-body interactions. New methods improve UCG model development for capturing system heterogeneities and phase coexistence.

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Area of Science:

Computational chemistry and biophysics
Materials science and condensed matter physics

Background:

Coarse-grained (CG) modeling bridges atomistic and larger scales but struggles with accuracy-efficiency trade-offs.
Incorporating many-body interactions in CG models is crucial for accuracy but computationally expensive.
Ultra Coarse-Graining (UCG) uses internal states to include many-body effects, but systematic model development remains challenging.

Purpose of the Study:

Develop synergistic methods for constructing bottom-up UCG models.
Enable UCG to capture atomistic system inhomogeneities, such as phase coexistence.
Improve the efficiency and transferability of UCG models for biomolecular systems.

Main Methods:

Systematic UCG force-field construction via relative entropy minimization.
Machine learning application for optimal local order parameters.
Application to methanol liquid-vapor interface and lipid bilayer systems.

Main Results:

Demonstrated a systematic approach for UCG force-field parameterization.
Utilized machine learning to enhance UCG model efficiency and transferability.
Successfully recapitulated phase coexistence phenomena using UCG modeling.

Conclusions:

The developed methods facilitate the creation of accurate and efficient UCG models.
UCG modeling can capture complex phenomena like phase coexistence, previously unobserved in CG simulations.
This work advances the application of UCG for studying heterogeneous biomolecular systems.