| name | molclaw-admet |
| description | Predict the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of the input molecules. |
| license | MIT license |
| metadata | {"skill-author":"PJLab"} |
ADMET Properties Prediction
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.
The description of tool pred_mol_admet.
Predict the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of the input molecules from smiles list or file.
Args:
smiles_list (List[str]): List of input SMILES strings, (e.g., ["N[C@@H](Cc1ccc(O)cc1)C(=O)O", "CC(C)C1=CC=CC=C1"]), default is []
smiles_file (str): Path to a file containing SMILES strings (TXT or CSV format), default is ''
Return:
status (str): success/error
msg (str): message
json_content (List[Dcit]): List of dict, each containing the keys 'smiles', 'physicochemical', 'druglikeness' and 'admet_predictions', where 'admet_predictions' includes over 90 key-value pairs representing various molecular properties
json_file (str): Path to the json file saving the ADMET prediction results
How to use tool pred_mol_admet :
response = await client.session.call_tool(
"pred_mol_admet",
arguments={
"smiles_list": smiles_list,
"smiles_file": ''
}
)
result = client.parse_result(response)
admet_predictions = result["json_content"]
