Pocket Location
SkillDev toolsUse P2Rank to locate binding pockets in the input protein. Unless specified by the user, prioritize using fpocket.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Pocket Location skill
What this skill tells your AI
The instructions your AI receives, as published by internscience/molclaw in skills/L1_tools/molclaw-p2rank/SKILL.md and read by ahel’s review.
Note:
- Local files are not directly accessible by the server. Please upload them to the server using
molclaw-file-transferbefore execution. - For PDB file inputs, it is recommended to preprocess them using
molclaw-pdbfixerbefore execution. - Please refer to skill
molclaw-scp-serverto complete tool invocation.
The description of tool pred_pocket_prank.
Use P2Rank to predict ligand binding pockets in the input protein.
Args:
pdb_file_path (str): Path to the protein structure file (PDB format)
Return:
status (str): success/error
msg (str): message
pred_pockets (List[dict]): List of dict, each containing pocket confidence and center position information. The first pocket (pred_pockets[0]) has the highest score and is usually used for molecular docking.
--site_id (str): Pocket id
--probability (float): Predicted confidence score (0~1) of the pocket
--center_x (float): Center X of the pocket
--center_y (float): Center Y of the pocket
--center_z (float): Center Z of the pocket
How to use tool pred_pocket_prank :
response = await client.session.call_tool(
"pred_pocket_prank",
arguments={
"pdb_file_path": pdb_file_path
}
)
result = client.parse_result(response)
pred_pockets = result["pred_pockets"]
Signals
- GitHub stars
- 33
- Forks
- 3
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
molclaw-p2rank- Source
- github.com/internscience/molclaw