用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Predict the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of the input molecules.
Predict binding affinity between target protein sequence and small molecule SMILES using Boltz-2.
Predict protein structures with Chai-1 from sequence or FASTA input and return model scoring summaries.
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基于 SOC 职业分类
| name | molclaw-hdock-tool |
| description | Run HDOCKlite docking for protein complexes and return run directories with ranked models. |
| license | MIT license |
| metadata | {"skill-author":"PJLab"} |
Note:
drugsda-file-transfer before execution.drugsda-fix_pdb before execution.The description of tool hdock_tool.
Run HDOCKlite protein docking and return the unique run directory, key files, and summary metrics for structure-based screening workflows.
Args:
receptor (str): Receptor PDB file path.
ligand (str): Ligand or partner PDB file path.
nmax (int): Number of docking models to generate (default 100).
no_complex (bool): Disable complex structure generation (default False).
angle (int): Rotation sampling interval in degrees (default 15).
rsite (str|None): Optional receptor binding-site residue file.
lsite (str|None): Optional ligand binding-site residue file.
Return:
status (str): success, partial_success, or error execution status.
msg (str): Human-readable execution summary.
output_dir (str): Unique run directory under tool_result/hdock_tool_result.
receptor (str): Resolved receptor input path.
ligand (str): Resolved ligand input path.
nmax (int): Effective model count upper bound used.
no_complex (bool): Effective no-complex flag used.
angle (int): Effective angle parameter used.
rsite (str|None): Effective receptor site file used.
lsite (str|None): Effective ligand site file used.
output_files (dict): Key generated file paths such as Hdock.out, topN.pdb, and best models.
metrics (dict): Summary metrics including generated model count and best docking score when available.
model_1.pdb is the top-ranked pose generated by createpl; model_2.pdb to model_10.pdb are sorted from better to worse by docking score.How to use tool hdock_tool :
response = await client.session.call_tool(
"hdock_tool",
arguments={
"receptor": "/path/to/receptor.pdb",
"ligand": "/path/to/ligand.pdb",
"nmax": 10,
"angle": 15
}
)
result = client.parse_result(response)
key_output = result["output_dir"]
# 1) Main mode: basic docking run (from README/test flow)
{
"receptor": "/path/to/receptor.pdb",
"ligand": "/path/to/ligand.pdb",
"nmax": 10,
"angle": 15,
"no_complex": False
}
# 2) Variant mode: light sampling with complex generation disabled and defined sites
{
"receptor": "/path/to/receptor.pdb",
"ligand": "/path/to/ligand.pdb",
"nmax": 5,
"angle": 10,
"no_complex": True,
"rsite": "/path/to/rsite.txt",
"lsite": "/path/to/lsite.txt"
}
# 3) Variant mode: exhaustive sampling with default complex outputs
{
"receptor": "/path/to/receptor.pdb",
"ligand": "/path/to/ligand.pdb",
"nmax": 100,
"angle": 15
}
After calling this tool, you MUST download all output structure files from the MCP server to the local workspace using server_file_to_base64. A tool call is NOT considered complete until its output files have been downloaded and verified locally (ls -la <file> — size must be > 0).
import base64, os
response = await client.session.call_tool(
"server_file_to_base64",
arguments={"file_path": result["output_file"]} # or relevant output field
)
dl = client.parse_result(response)
local_path = "stepNN_descriptive_name.ext"
with open(local_path, "wb") as f:
f.write(base64.b64decode(dl["base64_string"]))
assert os.path.getsize(local_path) > 0, f"Download failed: {local_path}"
Download policy: All structure output files are Category A (user-critical) — essential for user verification, downstream analysis, and reproducibility. When in doubt, download. Over-collection is always preferred over under-collection.
Specific files to download from HDOCK output: All ranked docked complex PDB models (typically model_1.pdb through model_10.pdb). At minimum, download the top-ranked model. These are Category A files essential for downstream ProLIF protein-protein analysis.