원클릭으로
molclaw-goca-tool
Run GoCa coarse-grained protein MD pipeline and collect key simulation artifacts from a unified run directory.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
메뉴
Run GoCa coarse-grained protein MD pipeline and collect key simulation artifacts from a unified run directory.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
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
}