molclaw-goca-tool

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"}

GoCa Pipeline

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 the managed wrapper to /data/lwj/wll/code/drug/GoCa/GoCa.

Usage

1. GoCa Pipeline

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"]

Example parameter sets

# 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
}