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Running Gaussian-accelerated Molecular Dynamics Simulations in NAMD [Article v1.0]
Haley M Michel1, Marcelo D Polêto1, Justin A Lemkul1,2
1Department of Biochemistry, Virginia Tech, Blacksburg, Virginia, 24061, United States.
Living Journal of Computational Molecular Science
|August 22, 2025
Summary
Gaussian-accelerated molecular dynamics (GaMD) enhances molecular simulations by reducing energy barriers for faster free energy landscape exploration. This tutorial provides a practical guide to GaMD simulations and analysis for biomolecular systems.
Area of Science:
- Computational chemistry
- Biophysics
- Molecular dynamics
Background:
- Enhanced sampling techniques are crucial for exploring complex biomolecular systems.
- Gaussian-accelerated molecular dynamics (GaMD) offers a method to overcome energy barriers and accelerate conformational sampling.
Purpose of the Study:
- To provide a comprehensive tutorial on applying GaMD simulations.
- To guide users through the complete GaMD workflow, from setup to analysis.
- To connect theoretical concepts of GaMD with practical implementation.
Main Methods:
- Demonstration of GaMD on the alanine dipeptide model system.
- Step-by-step instructions for conventional MD, GaMD equilibration, production, and reweighting.
- Utilizing PyReweighting for free energy profile analysis.
Main Results:
- Practical insights into input file preparation and GaMD convergence monitoring.
- Successful application of GaMD to accelerate sampling of configurational space.
- Generation of free energy profiles using reweighted data.
Conclusions:
- GaMD is an effective technique for enhanced sampling in molecular dynamics.
- This tutorial streamlines the GaMD workflow for researchers.
- The methodology is applicable to a wide range of biomolecular systems.
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