ADMET Properties Prediction
SkillDev toolsPredict the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of the input molecules.
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 ADMET Properties Prediction skill
What this skill tells your AI
The instructions your AI receives, as published by internscience/molclaw in skills/L1_tools/molclaw-admet/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_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]): Required list of input SMILES strings; pass [] when using smiles_file
smiles_file (str): Required path to a TXT/CSV SMILES file; pass '' when using smiles_list
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"]
Signals
- GitHub stars
- 33
- Forks
- 3
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
molclaw-admet- Source
- github.com/internscience/molclaw