msinclair-py

Build simulation-ready molecular systems with rust_simulation_tools' SystemBuilder — load force fields, read PDB/mol2 structures, combine protein+ligand, solvate in explicit water, add counterions/salt, and write AMBER prmtop/inpcrd/PDB. Use for "build a system", "solvate", "add ions", "explicit/implicit solvent", "protein-ligand complex", or "write prmtop".

Score predicted protein-protein interfaces with rust_simulation_tools — compute ipSAE, pDockQ, pDockQ2, LIS, and ipTM from a PDB/CIF structure plus pLDDT and PAE, or directly from in-memory arrays. Use for "ipSAE", "pDockQ", "interface confidence", "scoring AlphaFold/Boltz/Chai complexes", "PAE-based interface score", or "LIS".

Energy-minimize an AMBER system with rust_simulation_tools — steepest-descent + conjugate-gradient minimization with optional positional restraints, configurable cycles/cutoff/convergence, and a full energy-component breakdown. Use for "minimize", "energy minimization", "relax the structure", "restrained minimization", or "minimize prmtop/inpcrd".

Compute binding free energies with rust_simulation_tools' MM-PBSA / MM-GBSA implementation — trajectory-averaged ΔG with Generalized Born or Poisson-Boltzmann solvation, single-frame energies, per-residue decomposition, and entropy corrections. Use for "binding free energy", "MM-PBSA", "MM-GBSA", "ΔG of binding", "GB/PB solvation energy", "per-residue decomposition", or "interaction entropy".

Parameterize small-molecule ligands with rust_simulation_tools' built-in antechamber — assign GAFF2 atom types and AM1-BCC or Gasteiger partial charges, write a parameterized mol2, or compute raw AM1 Mulliken charges. Use for "parameterize a ligand", "GAFF2 atom types", "AM1-BCC charges", "antechamber", "Gasteiger charges", or "AM1 charges".

Analyze MD trajectories and topologies with rust_simulation_tools — VMD-style atom selections with property access, SASA (per-atom/per-residue/trajectory), Kabsch alignment, PBC unwrapping, and per-residue LJ/electrostatic interaction fingerprints. Use for "select atoms", "atom selection", "SASA", "solvent accessible surface", "align trajectory", "RMSD fit", "unwrap", "PBC", or "interaction fingerprint".

Overview and entry point for the rust_simulation_tools Python package (high-performance MD analysis written in Rust/PyO3). Use when the user wants to install/build the package, load AMBER topologies/coordinates/trajectories, or needs to know which capability-specific skill (system building, ligand parameterization, trajectory analysis, MM-PBSA, minimization, ipSAE) to reach for.

Analyze protein-protein/ligand interactions from MD trajectories with molecular-simulations — per-residue interaction-energy fingerprinting (electrostatic + Lennard-Jones), linear interaction energy (static structure or dynamic trajectory), and KMeans clustering of per-frame feature data. Use when characterizing binding interfaces, footprinting which residues drive an interaction, computing chain-chain interaction energies, or clustering conformations/fingerprints.

Score predicted protein complex interfaces with molecular-simulations' ipSAE — computes ipSAE, ipTM, pDockQ, pDockQ2, and LIS per chain pair from a predicted structure plus its pLDDT/PAE confidence arrays. Use when ranking or filtering AlphaFold-Multimer / Boltz / Chai docking predictions by interface confidence, or batch-scoring many predicted models.

Compute solvent-accessible surface area on a structure or MD trajectory with molecular-simulations — absolute per-residue SASA (Shrake-Rupley) and RelativeSASA fractional exposure (0=buried, 1=exposed). Use when measuring residue burial/exposure, finding solvent-exposed surfaces or buried interfaces, or quantifying conformational changes in accessibility over a trajectory.

Build AMBER molecular systems (topology + coordinates) for OpenMM simulations with molecular-simulations. Use when preparing a protein, protein-ligand complex, or implicit-solvent system from a PDB/CIF — solvating, neutralizing/ionizing to 150 mM NaCl, parameterizing small molecules with GAFF2, or assigning chains/disulfides before running MD.

Configure Parsl to deploy molecular-simulations builds, MD runs, and analyses across HPC. Use when running many systems/replicas in parallel, picking a compute platform (Local single-node GPU, Heterogeneous GPU+CPU, Polaris, or Aurora via PBSPro), pinning workers to GPUs, or writing/loading a YAML settings file for a cluster job.

Run OpenMM molecular dynamics with molecular-simulations — explicit-solvent NPT, implicit-solvent GB, energy minimization, and MM-PBSA binding free energy. Use when launching, configuring, or restarting an MD production run from AMBER/CHARMM inputs, choosing equilibration/production step counts, or selecting GPU/CPU platforms. For running many replicas across HPC nodes, combine with the parsl-hpc skill.