| name | molclaw-openawsem-tool |
| description | Runs OpenAWSEM simulations and extracts representative trajectory frames for downstream ensemble analysis. |
| license | MIT license |
| metadata | {"skill-author":"PJLab"} |
OpenAWSEM Simulation and Trajectory Extraction
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.
Usage
1. OpenAWSEM Simulation
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"]
Example parameter sets
{
"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"
}
{
"pdb": "relative/path/to/input.pdb",
"steps": 50000,
"mode": "nvt",
"temperature": 310.0,
"platform": "CPU",
"dry_run": True
}
2. OpenAWSEM Trajectory Frame Extraction
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"]
Example parameter sets
{
"sim_dir": "/path/to/awsem_sim_dir",
"num_frames": 100,
"backend": "auto",
"dry_run": False
}
{
"sim_dir": "relative/path/to/awsem_sim_dir",
"times": [0.0, 50.0, 100.0],
"backend": "mdtraj",
"dry_run": True
}
3. Simulation to Extraction Workflow
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()
