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 Reviewed versions: OpenMM 8.6.1 and MDAnalysis 2.10.0. Reference platform smoke checks use small synthetic systems; GPU performance and scientific convergence are not established by them. OpenMM latest API pages identify a development build, so the installed 8.6.1 API is the executable reference. Installation into a dedicated environment: 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 Examples require system specific preparation and validation. Review biological assembly, alternate locations, missing loops, termini, protonation, disulfides, ligands and cofactors before parameterization. An MD trajectory alone does not establish binding free energy or residence time. The functions below form one Python module: execute their import blocks together. Use a new output prefix for every stage to avoid overwriting earlier results. 1. System Preparation 2. Energy Minimization 3. NVT Equilibration 4. NPT Equilibration and Production Call this function first with a dedicated NPT equilibration prefix. Inspect density, energy, structure and replicate stability before a separate production call; the default duration is an example, not an equilibration or convergence criterion. Trajectory Analysis with MDAnalysis 1. Load Trajectory Use the solvated topology with exactly the DCD atom count and order (e.g. the minimized.pdb above), not the original unsolvated input. MDAnalysis converts lengths to Å and time to ps by default; OpenMM bare coordinates use nm. Preserve frame box vectors and actual timestamps; do not infer time from frame number. 2. RMSD Analysis 3. RMSF Analysis (Per Residue Flexibility) Make molecules whole and align a separate structural analysis copy before RMSF; RMSF does not align. Do not run periodic contacts on a rotated trajectory whose box was not rotated. See [analysis reference](references/mdanalysis analysis.md) for alignment, PCA, DSSP, hydrogen bonds and population derived free energy. 4. Protein Ligand Contacts Force Fields and Preparation Choose a validated protein/ligand/water/ion combination for the scientific system. The working example retains AMBER14/TIP3P FB; it is not a universal recommendation. Current OpenMM also bundles amber19 all.xml (ff19SB, DNA OL21, RNA OL3, lipid21), and charmm36 2024.xml with its own charmm36 2024/water.xml . Generic TIP3P and CHARMM modified TIP3P are not interchangeable. IDP ensembles are especially sensitive to protein water balance. Four site waters need extra particles and a matching Modeller geometry, unlike the three site example above. AMBER protein XML does not parameterize arbitrary ligands. Use a reviewed GAFF2 or OpenFF route with explicit stereochemistry, protonation, bond orders, atom mapping and charge method. A ligand only Interchange is not a protein ligand system. See [preparation reference](references/system preparation.md) for conservative PDBFixer and OpenFF examples, installation requirements and current release details. Validation and Provenance Start with minimization; finite energy does not establish a valid structure. Use staged NVT → NPT equilibration → production. This example has no restraints. A 2 fs step with constrained H containing bonds is a starting choice. Larger steps/HMR require integrator, stability and observable validation for that system. Use per frame boxes for periodic distances. Make molecules whole for structural observables using trusted bond topology; unwrapping cannot infer missing bonds. Assess burn in, autocorrelation, effective samples, replicas and uncertainties. Short stable temperature/density traces do not establish conformational sampling. Save topology/atom order, System/Integrator XML, force field files/versions, seeds, platform/precision, parameters and analysis selections. Checkpoints are platform/hardware/version specific; XML states are more portable but do not retain all internal random generator state. Test restarting the actual setup. 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