Run and analyze molecular dynamics simulations with OpenMM and MDAnalysis. Set up protein/small molecule systems, define force fields, run energy minimization and production MD, analyze trajectories (RMSD, RMSF, contact maps, free energy surfaces). For structural biology, drug binding, and biophysic

Molecular Dynamics Overview Molecular dynamics (MD) simulation computationally models the time evolution of molecular systems by integrating Newton's equations of motion. This skill covers two complementary tools: OpenMM (https://openmm.org/): High performance MD simulation engine with GPU support, Python API, and flexible force field support MDAnalysis (https://mdanalysis.org/): Python library for reading, writing, and analyzing MD trajectories from all major simulation packages Installation: When to Use This Skill Use molecular dynamics when: Protein stability analysis : How does a mutation affect protein dynamics? Drug binding simulations : Characterize binding mode and residence time of a ligand Conformational sampling : Explore protein flexibility and conformational changes Protein protein interaction : Model interface dynamics and binding energetics RMSD/RMSF analysis : Quantify structural fluctuations from a reference structure Free energy estimation : Compute binding free energy or conformational free energy Membrane simulations : Model proteins in lipid bilayers Intrinsically disordered proteins : Study IDR conformational ensembles Core Workflow: OpenMM Simulation 1. System Preparation 2. Energy Minimization 3. NVT Equilibration 4. NPT Equilibration and Production Trajectory Analysis with MDAnalysis 1. Load Trajectory 2. RMSD Analysis 3. RMSF Analysis (Per Residue Flexibility) 4. Protein Ligand Contacts Force Field Selection Guide System Recommended Force Field Water Model 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) GAFF2 for Small Molecules (via OpenFF Toolkit) 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

molecular-dynamics