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molclaw-openawsem-tool
Runs OpenAWSEM simulations and extracts representative trajectory frames for downstream ensemble analysis.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Runs OpenAWSEM simulations and extracts representative trajectory frames for downstream ensemble analysis.
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-openawsem-tool |
| description | Runs OpenAWSEM simulations and extracts representative trajectory frames for downstream ensemble analysis. |
| license | MIT license |
| metadata | {"skill-author":"PJLab"} |
Note:
molclaw-file-transfer before execution.molclaw-pdbfixer before execution.molclaw-scp-server to complete tool invocation.The description of tool openawsem_sim.
Run OpenAWSEM coarse-grained protein simulation for annealing or NVT workflows in structure screening and folding studies.
Args:
sim_dir (str|None): Simulation directory containing *-openmmawsem.pdb or *_openmmawsem.pdb, default None.
pdb (str|None): PDB file path or PDB ID used by awsem_create when sim_dir is not provided, default None.
steps (float): Simulation step count, default 1e5.
mode (str): Temperature control mode in {annealing, nvt}, default annealing.
temperature (float): NVT temperature in Kelvin passed to source script argument --temperature, default 300.0.
platform (str): OpenMM platform in {CPU, CUDA, OpenCL}, default CPU.
use_frag_mem (bool): Whether to use fragment memory instead of single memory, default False.
compute_q (bool): Whether to enable Q-value related terms when available, default False.
dry_run (bool): Whether to validate setup without running MD steps, default False.
gpu_id (str): GPU device index for CUDA/OpenCL platform, default 0.
Return:
status (str): success, error, or partial_success execution status.
msg (str): Human-readable execution summary.
output_dir (str): Unique run directory under tool_result/openawsem_result.
simulation_dir (str): Effective simulation directory used by the delegated source script.
steps (float): Effective step count used in this run.
mode (str): Effective simulation mode used in this run.
temperature (float): Effective NVT temperature used in this run.
platform (str): Effective compute platform used in this run.
dry_run (bool): Effective dry-run flag used in this run.
output_files (dict): Key output file paths such as final PDB, energy log, checkpoint, and trajectory files.
metrics (dict): Parsed summary metrics such as energy log line count and last log line when available.
How to use tool openawsem_sim :
response = await client.session.call_tool(
"openawsem_sim",
arguments={
"sim_dir": "/path/to/awsem_sim_dir",
"steps": 1000,
"mode": "annealing",
"temperature": 300.0,
"platform": "CUDA",
"use_frag_mem": False,
"compute_q": False,
"dry_run": False,
"gpu_id": "0"
}
)
result = client.parse_result(response)
simulation_dir = result["simulation_dir"]
# 1) Main mode
{
"sim_dir": "/path/to/awsem_sim_dir",
"steps": 1000,
"mode": "annealing",
"temperature": 300.0,
"platform": "CUDA",
"use_frag_mem": False,
"compute_q": False,
"dry_run": False,
"gpu_id": "0"
}
# 2) Variant mode
{
"pdb": "relative/path/to/input.pdb",
"steps": 50000,
"mode": "nvt",
"temperature": 310.0,
"platform": "CPU",
"dry_run": True
}
The description of tool openawsem_traj_extract.
Extracts representative structures from OpenAWSEM trajectories for downstream ensemble analysis and screening.
Args:
sim_dir (str): OpenAWSEM simulation directory containing trajectory and topology files.
num_frames (int): Number of evenly spaced structures to extract when times is not provided, default 100.
times (List[float]|None): Explicit extraction time points in picoseconds, default None.
backend (str): Trajectory backend in {mdtraj, mdanalysis, auto}, default auto.
dry_run (bool): Validate file discovery and prepare output directory without extraction, default False.
Return:
status (str): success, error, or partial_success execution status.
msg (str): Human-readable extraction summary.
output_dir (str): Unique run directory under tool_result/openawsem_result.
extracted_dir (str): Directory containing extracted PDB frames.
sim_dir (str): Resolved simulation directory.
trajectory_path (str|None): Detected trajectory file path.
topology_path (str|None): Detected topology file path.
frame_count (int): Number of extracted frame files.
frame_files (List[str]): Extracted PDB file paths.
index_file (str|None): Extraction index text file path.
How to use tool openawsem_traj_extract :
response = await client.session.call_tool(
"openawsem_traj_extract",
arguments={
"sim_dir": "/path/to/awsem_sim_dir",
"num_frames": 100,
"backend": "auto",
"dry_run": False
}
)
result = client.parse_result(response)
frame_files = result["frame_files"]
# 1) Main mode
{
"sim_dir": "/path/to/awsem_sim_dir",
"num_frames": 100,
"backend": "auto",
"dry_run": False
}
# 2) Variant mode
{
"sim_dir": "relative/path/to/awsem_sim_dir",
"times": [0.0, 50.0, 100.0],
"backend": "mdtraj",
"dry_run": True
}
Use openawsem_sim first, then feed its simulation_dir into openawsem_traj_extract.
client = DrugSDAClient("http://180.184.86.2:32208/mcp")
if not await client.connect():
print("connection failed")
return
sim_resp = await client.session.call_tool(
"openawsem_sim",
arguments={
"sim_dir": "/path/to/awsem_sim_dir",
"steps": 1000,
"mode": "annealing",
"platform": "CUDA",
"dry_run": False
}
)
sim_result = client.parse_result(sim_resp)
extract_resp = await client.session.call_tool(
"openawsem_traj_extract",
arguments={
"sim_dir": sim_result["simulation_dir"],
"num_frames": 100,
"backend": "auto",
"dry_run": False
}
)
extract_result = client.parse_result(extract_resp)
frame_files = extract_result["frame_files"]
await client.disconnect()