--|------------------------|-------------|
| Standard proteins | AMBER14 (amber14-all.xml) | TIP3P-FB |
| Proteins + small molecules | AMBER14 + GAFF2 | TIP3P-FB |
| Membrane proteins | CHARMM36m | TIP3P |
| Nucleic acids | AMBER99-bsc1 or AMBER14 | TIP3P |
| Disordered proteins | ff19SB or CHARMM36m | TIP3P |
System Preparation Tools
PDBFixer (for raw PDB files)
from pdbfixer import PDBFixer
from openmm.app import PDBFile
def fix_pdb(input_pdb, output_pdb, ph=7.0):
"""Fix common PDB issues: missing residues, atoms, add H, standardize."""
fixer = PDBFixer(filename=input_pdb)
fixer.findMissingResidues()
fixer.findNonstandardResidues()
fixer.replaceNonstandardResidues()
fixer.removeHeterogens(True) # Remove water/ligands
fixer.findMissingAtoms()
fixer.addMissingAtoms()
fixer.addMissingHydrogens(ph)
with open(output_pdb, 'w') as f:
PDBFile.writeFile(fixer.topology, fixer.positions, f)
return output_pdb
GAFF2 for Small Molecules (via OpenFF Toolkit)
# For ligand parameterization, use OpenFF toolkit or ACPYPE
# pip install openff-toolkit
from openff.toolkit import Molecule, ForceField as OFFForceField
from openff.interchange import Interchange
def parameterize_ligand(smiles, ff_name="openff-2.0.0.offxml"):
"""Generate GAFF2/OpenFF parameters for a small molecule."""
mol = Molecule.from_smiles(smiles)
mol.generate_conformers(n_conformers=1)
off_ff = OFFForceField(ff_name)
interchange = off_ff.create_interchange(mol.to_topology())
return interchange
Best Practices
- Always minimize before MD: Raw PDB structures have steric clashes
- Equilibrate before production: NVT (50–100 ps) → NPT (100–500 ps) → Production
- Use GPU: Simulations are 10–100× faster on GPU (CUDA/OpenCL)
- 2 fs timestep with HBonds constraints: Standard; use 4 fs with HMR (hydrogen mass repartitioning)
- Analyze only equilibrated trajectory: Discard first 20–50% as equilibration
- Save checkpoints: MD runs can fail; checkpoints allow restart
- Periodic boundary conditions: Required for solvated systems
- PME for electrostatics: More accurate than cutoff methods for charged systems
Additional Resources
- OpenMM documentation: https://openmm.org/documentation.html
- MDAnalysis user guide: https://docs.mdanalysis.org/
- GROMACS (alternative MD engine): https://manual.gromacs.org/
- NAMD (alternative): https://www.ks.uiuc.edu/Research/namd/
- CHARMM-GUI (web-based system builder): https://charmm-gui.org/
- AmberTools (free Amber tools): https://ambermd.org/AmberTools.php
- OpenMM paper: Eastman P et al. (2017) PLOS Computational Biology. PMID: 28278240
- MDAnalysis paper: Michaud-Agrawal N et al. (2011) J Computational Chemistry. PMID: 21500218