Menu
Generate new peptide molecules sampling from the input peptide sequence.
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
Baseado na classificação ocupacional SOC
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 new molecules de novo.
| name | molclaw-peptide-sampling |
| description | Generate new peptide molecules sampling from the input peptide sequence. |
| license | MIT license |
| metadata | {"skill-author":"PJLab"} |
Note:
molclaw-file-transfer before execution.molclaw-pdbfixer before execution.molclaw-scp-server to complete tool invocation.The description of tool pepinvent_peptide_sampling_by_peptide.
Generate new peptide molecules sampling from the input peptide sequence.
Args:
peptide (str): SMILES representation of a peptide sequence, with amino acid residues separated by '|?|', e.g., 'N[C@@H](CCCCN)C(=O)|?|N[C@@H](CC(C)C)C(=O)|?|N[C@@H](CCCNC(=N)N)C(=O)'
n (int): Number of molecules for sampling
filter_preset (str): Filter preset, options: ['none', 'minimal', 'default', 'strict'], default is 'default'
mw_min (float): Minimum molecular weight, default is 0.0
mw_max (float): Maximum molecular weight, default is 0.0
Return:
status (str): success/error
msg (str): message
save_smiles_file (str): Path to the saved SMILES file
output_smiles_list (List[str]): List of generated SMILES strings
How to use tool pepinvent_peptide_sampling_by_peptide :
response = await client.session.call_tool(
"pepinvent_peptide_sampling_by_peptide",
arguments={
"peptide": smiles,
"n": n,
"filter_preset": filter_type,
"mw_min": mw_min,
"mw_max": mw_max
}
)
result = client.parse_result(response)
output_smiles_list = result["output_smiles_list"]