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molclaw-goca-tool
Run GoCa coarse-grained protein MD pipeline and collect key simulation artifacts from a unified run directory.
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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Run GoCa coarse-grained protein MD pipeline and collect key simulation artifacts from a unified run directory.
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。
基于 SOC 职业分类
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.
Chroma toolkit skill covering chroma_monomer for single-chain generation, chroma_complex for multi-chain assembly generation, and chroma_symmetry for symmetry-constrained protein design.
Retrieve SMILES strings from PubChem database using compound names.
Generate new molecules de novo.
| name | molclaw-goca-tool |
| description | Run GoCa coarse-grained protein MD pipeline and collect key simulation artifacts from a unified run directory. |
| license | MIT license |
| metadata | {"skill-author":"PJLab"} |
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.
GoCa executable path is fixed by wrapper to /root/lwj/wll/code/drug/GoCa/GoCa.
The description of tool goca_pipeline.
Runs GoCa coarse-grained setup and optional full MD workflow for protein structure relaxation and trajectory generation.
Args:
protein_pdb (str): Input protein PDB path, required.
full_md (bool): Whether to run EM, production MD, and post-processing, default True.
temperature (float): GoCa reduced temperature used for MD, default 45.0.
md_time (float): MD simulation length in ps, default 12000.0.
gpu_ids (str | None): Optional GROMACS GPU device IDs, default None.
dry_run (bool): Create tracked run directory and return normalized parameters without execution, default False.
Return:
status (str): success, partial_success, or error.
msg (str): Human-readable run summary.
output_dir (str): Run-specific directory under tool_result/goca_pipeline_result.
work_dir (str): Relative GoCa working directory under output_dir.
protein_pdb (str): Resolved input protein PDB absolute path.
full_md (bool): Effective full_md value used by wrapper.
temperature (float): Effective reduced temperature used by wrapper.
md_time (float): Effective MD time in ps used by wrapper.
gpu_ids (str | None): Effective GPU IDs used by wrapper.
dry_run (bool): Effective dry_run value used by wrapper.
key_files (dict): Key output files relative to output_dir.
analysis_dir (str | None): Analysis directory relative to output_dir when generated.
How to use tool goca_pipeline :
response = await client.session.call_tool(
"goca_pipeline",
arguments={
"protein_pdb": "/path/to/input.pdb",
"full_md": True,
"md_time": 1000.0,
"temperature": 45.0,
"gpu_ids": None,
"dry_run": False
}
)
result = client.parse_result(response)
key_output = result["output_dir"]
# 1) Main mode
{
"protein_pdb": "/path/to/input.pdb",
"full_md": True,
"md_time": 1000.0,
"temperature": 45.0,
"gpu_ids": None,
"dry_run": True
}
# 2) Variant mode
{
"protein_pdb": "relative/path/to/protein.pdb",
"full_md": False,
"md_time": 50000.0,
"temperature": 50.0,
"gpu_ids": "0",
"dry_run": False
}