Molclaw Admet

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 predmoladmet.

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 predmoladmet :

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"]

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: InternScience
• Source: InternScience/MolClaw
• License: MIT

Install and usage instructions live in the source repository linked above.