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AntiFold

0.3.1

Design antibody sequences from structure with AI-powered inverse folding Learn more

Input

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0 credits

Output

Configure inputs to begin

Set options on the left, then click “Submit job”.

AntiFold webserver overview

AntiFold 0.3.1 performs antibody-specific inverse folding on a fixed variable-domain structure. It supports paired heavy and light variable domains, nanobodies, optional antigen context, IMGT region masks, probability analysis, sequence sampling, and native per-residue embeddings.

Each run returns AntiFold's residue-level amino-acid distribution and run files. Sampling runs also return designed antibody sequences with source-native scores. For method background, preparation guidance, interpretation, and validation, see how to use AntiFold online.

Pricing

JobCreditsAssumptions
One antibody or nanobody structure30One .pdb, .ent, or .cif input. The current quote is unchanged by sequence count, temperature, region selection, antigen context, or embedding extraction.

The exact credit quote is calculated before submission. A workflow that submits multiple structures creates one quoted AntiFold job per structure.

Inputs

InputAccepted dataLimitNotes
Antibody Structure.pdb, .ent, .cif, or an RCSB PDB fetch50 MiBPaired mode requires at least two protein chains. Nanobody mode accepts a single VHH chain.

The structure should contain antibody variable domains. Region-specific sampling uses the structure's IMGT residue numbering. AntiFold reports a warning when the numbering does not appear compatible instead of silently renumbering the structure.

Chain IDs can use any valid labels. In paired mode, blank heavy and light chain fields select the first and second non-antigen chains in file order. In nanobody mode, a single available chain can be selected automatically. A declared antigen chain is used as structural context and cannot also be assigned an antibody role.

Settings

Core settings

ParameterTypeDefaultDescription
Input modeenumPaired antibody (VH/VL)Selects paired heavy/light or Nanobody / VHH processing.
Heavy chain IDstringautomaticOptional paired-mode heavy-chain label. Blank selects the first non-antigen chain.
Light chain IDstringautomaticOptional paired-mode light-chain label. Blank selects the second non-antigen chain.
Nanobody chain IDstringautomaticOptional nanobody-mode VHH chain label. A single available chain is selected automatically.
Antigen chain IDstringoptionalIncludes one antigen chain as structural context. Sampling remains limited to the selected antibody chain or chains.
Number of sequencesinteger0Generates 0 to 100 variants. 0 runs the source-default probability analysis without sequence sampling.
Sampling temperaturenumber0.2Accepts 0 to 1.5. Lower values concentrate sampling on high-probability amino acids; higher values increase diversity.

IMGT region selection

ParameterTypeDefaultDescription
IMGT regions to designenumCDRs only (CDR1, CDR2, CDR3)Selects the source-native region mask used for sequence sampling.

Available aggregate masks are:

  • cdrs: all CDR1, CDR2, and CDR3 positions
  • all: all antibody variable-domain regions
  • heavy_cdrs and light_cdrs: all CDRs on one chain
  • CDR1, CDR2, and CDR3: the named CDR on both applicable chains
  • frameworks: all framework regions
  • heavy_all and light_all: all regions on one chain

Chain-specific masks are CDRH1, CDRH2, CDRH3, CDRL1, CDRL2, CDRL3, FWH1, FWH2, FWH3, FWH4, FWL1, FWL2, FWL3, and FWL4. Light-chain masks are unavailable in nanobody mode.

Advanced options

ParameterTypeDefaultDescription
Random seedinteger42Accepts 0 to 4,294,967,295 and controls sequence sampling. Seeded FASTA designs are stable on the reviewed runtime, while final GPU probability digits may vary.
Extract per-residue embeddingsbooleanfalseReturns AntiFold's native per-residue .npy representation. AntiFold 0.3.1 requires Number of sequences to be 0 when this option is enabled.

Outputs

OutputFormatWhen returnedContents
Residue probabilities.csvEvery successful runStructure chain and position, insertion code, original and top residue, IMGT region, perplexity, and log probabilities for all 20 standard amino acids.
Designed sequences.fastaNumber of sequences is greater than 0Original and sampled antibody sequences with temperature, sample number, score, global score, sequence recovery, and mutation count in the native headers.
Per-residue embeddings.npyEmbedding extraction is enabledSource-native float32 latent representation, preserved as binary NumPy data.
Structured results.jsonEvery successful runParsed residue rows, sampled sequence metadata, mutations, summary values, and source provenance.
Run log.txtEvery successful runAntiFold's native execution log and scientific warnings.

The Results view compares sampled sequences with the submitted sequence. The Residue probabilities view presents the native CSV as a spreadsheet. Every native file remains downloadable from the Files view and can be routed through workflows where its format is supported.

Understanding results

  • top_res is the highest-probability amino acid at a residue position.
  • The amino-acid columns contain source-native log probabilities. A larger value, meaning closer to zero, indicates greater model support at that position.
  • perplexity is the effective breadth of the residue distribution. Lower values indicate a concentrated distribution; higher values indicate more alternatives. Compare positions within the same run rather than applying a universal pass or fail threshold.
  • score is the sampled sequence's mean negative log-likelihood over the selected design region. global_score uses all selected antibody residues. Lower values indicate stronger model support, but neither value is an experimental affinity or stability measurement.
  • seq_recovery is the fraction of sampled antibody positions that match the submitted sequence. Mutation records use the native structure chain, residue number, and insertion code.

AntiFold assumes a fixed input backbone. A sequence with a favorable score still requires independent structural, developability, binding, and experimental validation for its intended use.

Table of contents

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