Install
$ agentstack add skill-learningmatter-mit-atomisticskills-drug-complex-system-builder ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
drug-complex-system-builder
Goal
To take a prepared protein (PDB) and a validated ligand pose (SDF) and produce a fully parameterized, solvated, ion-neutralized OpenMM simulation bundle ready for [drug-protein-ligand-md](../drug-protein-ligand-md/SKILL.md).
The output bundle includes:
- Serialized OpenMM System XML (force field parameters, constraints)
- Full-precision initial state XML (positions + box vectors for exact restart)
- Solvated PDB with protein + ligand + water + ions (for visualization)
- Provenance JSON recording all build parameters
Instructions
1. Prepare inputs
Required inputs:
- Receptor PDB: from [drug-protein-prep](../drug-protein-prep/SKILL.md) (protonated, missing residues resolved).
- Ligand SDF: from [drug-pose-validation](../drug-pose-validation/SKILL.md) or [drug-docking-vina](../drug-docking-vina/SKILL.md). Must have 3D coordinates in the receptor frame and explicit hydrogens.
2. Build the solvated complex
# Env: drugmd-agent
python .agents/skills/drug-complex-system-builder/scripts/build_complex.py \
--receptor docking/inputs/protein_prepared.pdb \
--ligand docking/validation/valid_poses.sdf \
--ligand_ff openff-2.2.0 \
--protein_ff amber/ff14SB \
--water_model tip3p \
--box_padding 12.0 \
--ionic_strength 0.15 \
--output_dir md/system/
Key parameters:
--ligand_ff: Force field for the ligand. Options:openff-2.2.0(Sage, recommended),gaff-2.11. OpenFF Sage is generally preferred for drug-like molecules.--protein_ff: Protein force field. Default:amber/ff14SB.--water_model: Water model. Default:tip3p. Options:tip3p,tip3pfb,tip4pew,opc,spce. Usetip3pfboropcfor better accuracy at higher cost.--box_padding: Minimum distance from solute to box edge in Angstroms (default: 12.0). Use 10-12 A for production; smaller values risk periodic image artifacts.--ionic_strength: Target NaCl concentration in mol/L (default: 0.15, physiological). The system is always charge-neutralized first; additional ion pairs are added to reach the target ionic strength. The ionic strength calculation does not count the neutralization ions (they are treated as bound to the solute).--pose_index: Which pose from the SDF to use (default: 0, the top-ranked pose).--box_shape: Simulation box geometry (default:cube). Options:cube,dodecahedron,octahedron. Dodecahedron and octahedron use ~30% less water for the same minimum solute-edge distance.--hydrogen_mass: Hydrogen mass in amu for hydrogen mass repartitioning (default: 4.0). With HMR (3-4 amu), the script usesAllBondsconstraints, enabling 4-5 fs timesteps (OpenMM recommends 5 fs withLangevinMiddleIntegrator). Set to 1.008 to disable HMR (usesHBondsconstraints, requires 2 fs timestep). Note: at 4 amu, methyl carbons become lighter than their bonded hydrogens, which can affect dynamics in some systems (particularly membranes). Use 3 amu if this is a concern. The downstream MD skill must use a matching timestep (checkhmr_enabledandconstraintsin the provenance JSON).
3. Inspect outputs
The script produces:
md/system/complex_solvated.pdb: solvated system for visualization (PDB precision: 0.001 A)md/system/system.xml: serialized OpenMM System (force field parameters, constraints)md/system/state_initial.xml: full-precision positions and box vectors for simulation restartmd/system/build_provenance.json: records all build parameters, atom counts, box dimensions, HMR status, constraint type
Visually inspect complex_solvated.pdb to verify:
- The ligand is in the expected binding pocket
- No steric clashes between protein and ligand
- Water fills the box uniformly
- Ions are distributed (not clustered)
4. Troubleshooting
Common issues:
- Ligand parameterization fails: ensure the ligand SDF has explicit hydrogens and correct bond orders. Re-run [drug-ligand-prep](../drug-ligand-prep/SKILL.md) if needed. The script assigns AM1-BCC partial charges automatically; any pre-existing charges in the SDF are overwritten to ensure deterministic behavior.
- Steric clash warning: the script checks minimum protein-ligand interatomic distances before solvation. If you see a clash warning, the docking pose may need refinement. Mild clashes (1.0-1.5 A) can often be resolved by energy minimization, but severe clashes (100 heavy atoms) or metal-containing compounds, parameterization may require manual intervention.
- Protein force field: Only Amber-family force fields (ff14SB, ff19SB) are supported through openmmforcefields. CHARMM support would require a different builder.
- Box shape: Defaults to cubic. Dodecahedron and truncated octahedron are supported via
--box_shape(requires OpenMM 8.0+).
References
- Maier, J. A.; Martinez, C.; Kasavajhala, K.; Wickstrom, L.; Hauser, K. E.; Simmerling, C. ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB. J. Chem. Theory Comput. 2015, 11, 3696-3713. https://doi.org/10.1021/acs.jctc.5b00255
- Boothroyd, S.; Behara, P. K.; Madin, O. C.; et al. Development and Benchmarking of Open Force Field 2.0.0: The Sage Small Molecule Force Field. J. Chem. Theory Comput. 2023, 19, 3251-3275. https://doi.org/10.1021/acs.jctc.3c00039
- Eastman, P.; Swails, J.; Chodera, J. D.; et al. OpenMM 7: Rapid Development of High Performance Algorithms for Molecular Dynamics. PLoS Comput. Biol. 2017, 13, e1005659. https://doi.org/10.1371/journal.pcbi.1005659
Author: Matthew Cox Contact: GitHub @mcox3406
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: learningmatter-mit
- Source: learningmatter-mit/AtomisticSkills
- License: MIT
- Homepage: https://arxiv.org/abs/2605.24002
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.