القائمة
Compute hydrogen bonding-related properties for a list of SMILES strings, specifically determining the number of hydrogen bond donors and acceptors for each input molecule.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Predict the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of the input molecules.
Predict binding affinity between target protein sequence and small molecule SMILES using Boltz-2.
Predict protein structures with Chai-1 from sequence or FASTA input and return model scoring summaries.
Chroma toolkit skill covering chroma_monomer for single-chain generation, chroma_complex for multi-chain assembly generation, and chroma_symmetry for symmetry-constrained protein design.
Retrieve SMILES strings from PubChem database using compound names.
Generate entirely new drug-like molecules from scratch without any starting molecule, using REINVENT4's de novo prior.
| name | molclaw-mol-hbond-metrics |
| description | Compute hydrogen bonding-related properties for a list of SMILES strings, specifically determining the number of hydrogen bond donors and acceptors for each input molecule. |
| license | MIT license |
| metadata | {"skill-author":"PJLab"} |
The description of tool calculate_mol_hbond.
Compute hydrogen bonding-related properties for each SMILES.
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"])
Return:
status (str): success/error
msg (str): message
metrics (List[dict]): List of dict, each containing several feature keys.
--smiles (str): A SMILES string of smiles_list
--num_h_donors (int): Number of hydrogen bond donors
--num_h_acceptors (int): Number of hydrogen bond acceptors
How to use tool calculate_mol_hbond:
response = await client.session.call_tool(
"calculate_mol_hbond",
arguments={
"smiles_list": smiles_list
}
)
result = client.parse_result(response)
metrics = result["metrics"]