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molclaw-peptide-sampling
Generate new peptide molecules sampling from the input peptide sequence.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Generate new peptide molecules sampling from the input peptide sequence.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
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"]