AntiBMPNN
Type anything; we’ll convert to a safe ID when you run.
Drop file here or click to upload
# API example will render hereShort label for this AntiBMPNN job; shown in dashboard/history; no effect on results.
Select which AntiBMPNN checkpoint to use. Different weights can shift sequence preferences and output diversity.
How many designs to sample in one run. Higher values explore more candidates but increase runtime and output size.
Controls how conservative or exploratory sampling is. Lower values stay closer to the model’s top choices, while higher values increase diversity.
Adds noise to the input backbone during sampling. Small amounts can increase diversity, while larger values may reduce fidelity to the starting structure.
Upload a PDB/CIF structure, or use Vici Lookup. We parse chains and residue numbering for design region selection.
Choose chain(s) and residue ranges to redesign. Up to 6 rows.
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