ProLIF Docking Pose Analysis Skill

SkillDev tools

ProLIF docking-pose analysis skill for batch interaction fingerprints and interaction count summaries.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the ProLIF Docking Pose Analysis Skill skill

What this skill tells your AI

The instructions your AI receives, as published by internscience/molclaw in skills/L1_tools/molclaw-prolif-docking/SKILL.md and read by ahel’s review.

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.
  • Please refer to skill molclaw-scp-server to 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

Batch-analyze multiple docking-generated binding poses and produce interaction fingerprints or interaction count summaries. Use this skill to screen binding modes and evaluate docking result quality.

Routing note: This tool is the primary choice for batch docking fingerprint comparison (≥ 2 poses). For single-structure deep analysis (one pose, one complex), use molclaw-interaction-visualizer instead — it provides Schrödinger-style 2D diagrams, PyMOL 3D renderings, and decision-ready JSON that this tool does not produce.

Input Source Mapping

ParameterSource Guidance
protein_pathGenerated by structure retrieval/prediction tools (e.g., retrieve_protein_structure_by_*, pred_protein_structure_esmfold, chai1_predict) or a PDB fixed by fix_pdb
ligand_pathsGenerated by docking tools (e.g., molecule_docking_quickvina_fullprocess, hdock_tool, karmadock_tool) as pose files (.sdf/.mol2/.pdbqt)
ligand_formatMust match the upstream docking output format: sdf, mol2, or pdbqt
template_smilesRequired when ligand_format is pdbqt to provide ligand chemistry reference

Usage

Tool: prolif_docking

Summarize docking poses with ProLIF and return a CSV of interaction fingerprints plus summary metrics.
Args:
    protein_path (str): Path to the receptor protein structure.
    ligand_paths (List[str]): List of ligand pose files.
    ligand_format (str): Ligand format identifier (e.g., 'sdf', 'mol2', 'pdbqt').
    template_smiles (str|None): Optional template SMILES; required when ligand_format is 'pdbqt'.
    interactions (List[str]|None): Optional interaction types to compute.
    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.
Return:
    status (str): 'success' or 'error'.
    msg (str): Human-readable summary or error message.
    command (str): The executed command label ('docking').
    output_dir (str|None): Run-specific directory under tool_result/prolif_result.
    output_file (str|None): Path to the produced CSV summary file.
    n_frames (int|None): Number of processed frames where applicable.
    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_docking

response = await client.session.call_tool(
    "prolif_docking",
    arguments={
        "protein_path": "relative/path/to/receptor.pdb",
        "ligand_paths": [
            "relative/path/to/pose1.sdf",
            "relative/path/to/pose2.sdf"
        ],
        "ligand_format": "sdf",
        "interactions": ["Hydrophobic", "HBDonor"]
    }
)
result = client.parse_result(response)
key_output = result["output_file"]

Example Parameter Sets

# 1) Main mode
{
    "protein_path": "relative/path/to/receptor.pdb",
    "ligand_paths": [
        "relative/path/to/docking_poses.sdf"
    ],
    "ligand_format": "sdf"
}

# 2) Variant mode
{
    "protein_path": "relative/path/to/receptor.pdb",
    "ligand_paths": [
        "relative/path/to/pose1.pdbqt",
        "relative/path/to/pose2.pdbqt"
    ],
    "ligand_format": "pdbqt",
    "template_smiles": "CCO",
    "count": True,
    "vicinity_cutoff": 4.0
}

Signals

GitHub stars
33
Forks
3
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
molclaw-prolif-docking
Source
github.com/internscience/molclaw