Molecular-dynamics (MD) simulations provide atom-level insight into biomolecular motion and are widely used to complement structure-guided drug discovery, ligand optimization, and mechanistic structural biology. However, reproducible MD remains technically challenging because users must coordinate structure cleanup, force-field-compatible topology generation, ligand parameterization, solvation, ionization, energy minimization, equilibration, production simulation, trajectory processing, and downstream interpretation; errors at any stage can compromise results and discourage non-expert users. Here, we present PyMACS, an open-source Python automation framework for GROMACS-based molecular dynamics using the CHARMM36 or CHARMM36/LJ-PME biomolecular force fields together with CGenFF-compatible small-molecule parameterization. PyMACS accepts common structural input formats, including PDB, CIF, and mmCIF files, and is designed to operate on a broad range of user-supplied biomolecular systems rather than being restricted to a single target class or experimentally resolved protein-ligand complexes. Compatible inputs include experimental structures, docked or model-derived complexes, computationally predicted biomolecular assemblies, apo proteins, protein-ligand systems, cofactor-containing complexes, peptide-protein assemblies, protein-protein complexes, RNA-, DNA-, and mixed nucleic-acid-protein systems for setup and simulation workflows when residue naming and CHARMM/GROMACS topology generation support the input, and PROTAC or other ternary-complex models when force-field compatibility requirements are met. The pipeline automates structure preparation, ligand and component handling, GROMACS topology generation, system assembly, solvation, ionization, equilibration, production MD, checkpoint-aware execution, and post-simulation analysis. PyMACS also converts completed trajectories into interpretable outputs including RMSD, RMSF, radius of gyration, ligand-stability metrics, residue-contact summaries, interaction-network visualizations, CSV exports, and report-ready figures. Designed for both interactive novice use and headless reproducible execution, PyMACS lowers the barrier to rigorous MD simulation while preserving configurable control over scientific parameters, computational resources, and analysis thresholds. By integrating setup, simulation, analysis, and visualization into a transparent workflow, PyMACS enables medicinal chemists and structural biology researchers to evaluate candidate binding hypotheses, compare biomolecular systems, and generate reproducible MD-derived evidence with substantially reduced manual overhead.
Schulz et al. (Wed,) studied this question.