Install
$ agentstack add skill-internscience-molclaw-molclaw-prolif-md ✓ 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.
About
ProLIF MD Interaction Fingerprinting Skill
Note:
- Local files are not directly accessible by the server. Please upload them to the server using
molclaw-file-transferbefore execution. - For PDB file inputs, it is recommended to preprocess them using
molclaw-pdbfixerbefore execution. - Please refer to skill
molclaw-scp-serverto complete tool invocation.
> [!NOTE] > Local files are not directly accessible by the server. Please upload them to the server using molclaw-file-transfer before execution. > For PDB file inputs, it is recommended to preprocess them using molclaw-pdbfixer before execution.
Task Description
Analyze protein-ligand interaction fingerprints in molecular dynamics (MD) trajectories, with support for frame slicing and residue controls. Use this skill to evaluate whether binding patterns remain stable throughout simulation.
> Routing note: This tool is the primary choice for MD trajectory interaction dynamics (multi-frame analysis). For single-structure analysis (one frame, one complex), use molclaw-interaction-visualizer instead.
Input Source Mapping
| Parameter | Source Guidance | |-----------|-----------------| | topology_path | Output topology file from MD workflow tools: e.g., protein_openmm_md, prepare_complex, prepare_protein_md, or goca_pipeline (.psf/.pdb/.prmtop) | | trajectory_path | Output trajectory file from the same MD workflow tools (.dcd/.nc/.xtc) | | ligand_selection | User-provided ligand selection string, for example resname LIG or resid 100-101 | | protein_selection | Defaults to protein; can be customized to narrow protein scope |
Usage
Tool: prolif_md
Compute ProLIF fingerprints for an MD trajectory and return standardized summary metrics.
Args:
topology_path (str): Path to the topology file (e.g., .psf, .pdb, .prmtop).
trajectory_path (str): Path to the trajectory file to analyze.
ligand_selection (str): Selection string identifying ligand atoms.
protein_selection (str): Selection string for protein atoms. Default: 'protein'.
interactions (List[str]|None): Optional interaction types to compute (e.g., Hydrophobic, HBDonor).
count (bool): If True, compute interaction counts instead of fingerprints. Default: False.
vicinity_cutoff (float|None): Optional distance cutoff for vicinity interactions.
params_json (str|None): Optional JSON parameter file path for ProLIF interaction settings.
start (int|None): Optional start frame index.
stop (int|None): Optional stop frame index (exclusive).
step (int|None): Optional frame stride.
residues (List[str]|None): Optional explicit residue list to include.
all_residues (bool): If True, include all residues in analysis. Default: False.
Return:
status (str): 'success' or 'error'.
msg (str): Human-readable summary or error message.
command (str): The executed command label ('md').
output_dir (str|None): Run-specific directory under tool_result/prolif_result.
output_file (str|None): Path to the generated CSV file.
n_frames (int|None): Number of processed frames.
n_interactions (int|None): Number of interaction columns in output.
frequent_interactions (List[dict]|None): High-frequency interactions (>30%) with keys 'interaction' and 'frequency'.
result_summary (dict|None): Full summary dictionary from the wrapper.
How To Use prolif_md
response = await client.session.call_tool(
"prolif_md",
arguments={
"topology_path": "relative/path/to/system.prmtop",
"trajectory_path": "relative/path/to/md_prod.nc",
"ligand_selection": "resname LIG",
"protein_selection": "protein",
"interactions": ["Hydrophobic", "HBDonor"],
"start": 0,
"stop": 100,
"step": 2
}
)
result = client.parse_result(response)
key_output = result["output_file"]
Example Parameter Sets
# 1) Main mode
{
"topology_path": "relative/path/to/system.prmtop",
"trajectory_path": "relative/path/to/md_prod.nc",
"ligand_selection": "resname LIG",
"protein_selection": "protein",
"interactions": ["Hydrophobic", "HBDonor", "HBAcceptor"],
"start": 0,
"stop": 100,
"step": 2
}
# 2) Variant mode
{
"topology_path": "relative/path/to/system.prmtop",
"trajectory_path": "relative/path/to/md_prod.nc",
"ligand_selection": "resname LIG",
"count": True,
"all_residues": True,
"vicinity_cutoff": 4.5,
"params_json": "relative/path/to/prolif_params.json"
}
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: InternScience
- Source: InternScience/MolClaw
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.