4.5. Using MD Packages#
4.5.1. Anatomy of an MD Simulation Workflow#
4.5.1.1. Initialization#
Create initial configuration and parameterize the force field.
Tools:
packmol
,mbuild/Foyer
,ambertools
, etc.
4.5.1.2. Equilibration#
Energy Minimization: Removes overlaps or poor initial configurations to prevent simulation instability.
Methods: Steepest Descent, Conjugate Gradient, L-BFGS, FIRE.
NVT Ensemble: Brings system to correct temperature.
Use aggressive thermostats (e.g., Isokinetic, Berendsen, Langevin).
Be cautious if initial velocities are zero (can cause divide-by-zero errors).
NPT Ensemble: Brings system to correct density.
Barostat usually has a longer time constant than thermostat.
Ensure momentum is zeroed when switching from non-conserving thermostats.
Simulate for multiple relaxation times to ensure equilibrium.
Use transport coefficients to estimate required time.
Monitor observables like energy (U), radial distribution function (g®), and density.
4.5.2. Production#
Run long enough to gather statistically independent samples of quantities of interest.
Trajectory dumping can be disk-intensive—choose frequency wisely.
Use checkpointing (saving restart files) to recover from hardware failures.
4.5.3. Post-processing#
Write scripts to compute properties, averages, etc., from simulation outputs.
Can be done on HPC clusters or downloaded to local machines.
Use existing tools and methods when possible—avoid reinventing the wheel.
4.5.4. Tips#
Choose the largest time step (Δt) that still ensures accurate integration—test this.
Tune hyperparameters for performance using representative simulations.
Run multiple simulation copies to improve statistics and estimate errors.
Organize files clearly during parameter sweeps. Example structure:
data/ ├── T-1.0/ │ ├── V-20/ │ │ └── input.sh │ ├── V-30/ │ │ └── input.sh ├── T-1.5/ │ ├── V-205/ │ └── V-301/
Consider using tools to manage simulation campaigns.
4.5.5. Recommended MD Packages#
GROMACS, NAMD, OpenMM, AMBER – widely used in biophysics.
LAMMPS, HOOMD-blue – general-purpose physics simulations.
Always read the documentation for your chosen tool carefully!
4.5.6. References#
“Simulations: The Dark Side,” Daan Frenkel, 2013 4
Braun, E., Gilmer, J., Mayes, H. B., Mobley, D. L. ., Monroe, J. I., Prasad, S., & Zuckerman, D. M. . (2018). Best Practices for Foundations in Molecular Simulations [Article v1.0]. Living Journal of Computational Molecular Science, 1(1), 5957. 13
In general, the Journal Living Journal of Computational Molecular Science has excellent how to articles, tutorials, and best practices.