At least one CDR loop length or range must be specified for RFantibody.
Click to upload (.pdb, .ent)
Click to upload (.pdb, .ent)
RFantibody is a structure-guided antibody and nanobody design pipeline built around an antibody-tuned version of RFdiffusion. It generates new CDR-mediated binding geometries against a chosen epitope, designs compatible loop sequences, and then filters the resulting complexes with an antibody-tuned RoseTTAFold2 model.
The method was introduced as a route to de novo, epitope-specific antibody design from structural input rather than immunization or random library discovery. In the published workflow, the computational design stage is followed by experimental screening, because the model can generate structurally accurate binders but still requires broad sampling to recover the strongest candidates.
ProteinIQ runs RFantibody on hosted GPU infrastructure, so the full three-stage pipeline can be launched from the browser without installing RosettaCommons dependencies locally.
The online interface accepts one target structure and one antibody or nanobody framework. The target can be uploaded as a PDB/ENT file or fetched from the RCSB. The framework must already be prepared in RFantibody's HLT format.
| Input | Description |
|---|---|
Target antigen structure | Antigen PDB or ENT structure, uploaded directly or fetched from the RCSB by PDB ID. Large targets should usually be truncated around the intended epitope because runtime scales poorly with target size. |
HLT antibody framework | Antibody or nanobody framework PDB in RFantibody HLT format. This is not a generic antibody structure file; it must use RFantibody chain conventions and CDR loop remarks. |
| Requirement | Description |
|---|---|
| Heavy chain | Must use chain ID H. For nanobodies, the single variable domain is treated as the heavy chain framework. |
| Light chain | If present, must use chain ID L. Nanobody frameworks omit this chain. |
| Chain order | Protein chains should appear in H then L order. In full HLT complexes upstream, target chains are represented as T. |
| Loop remarks | The file must end with REMARK PDBinfo-LABEL annotations that mark the absolute residue indices of the CDR loops, for example REMARK PDBinfo-LABEL: 32 H1. |
| Accepted examples | Upstream example frameworks include the nanobody file h-NbBCII10.pdb and the antibody Fv file hu-4D5-8_Fv.pdb. |
Generic antibody PDB files usually do not include those loop remarks or chain conventions. In the upstream RFantibody workflow, such structures are converted to HLT format before design.
| Setting | Description |
|---|---|
Backbone designs | Number of backbone dock designs to generate in the RFdiffusion stage (1-10, default 1). |
Sequences per backbone | Number of ProteinMPNN sequence variants to sample for each designed backbone (1-8, default 2). |
Sequence temperature | ProteinMPNN sampling temperature (0.1-1.0, default 0.2). Lower values bias toward more conservative loop sequences. |
RF2 recycles | Number of RoseTTAFold2 recycling iterations used during filtering (1-20, default 10). |
Deterministic mode | Requests deterministic sampling where supported, useful for reproducible pilot runs. |
| Setting | Description |
|---|---|
H1 length | Heavy-chain CDR1 length or length range, such as 7 or 5-8. |
H2 length | Heavy-chain CDR2 length or length range. |
H3 length | Heavy-chain CDR3 length or length range. Longer H3 values expand the search space and are often used when deeper pockets must be reached. |
L1 length | Optional light-chain CDR1 range for antibody frameworks. This should be left blank for nanobody frameworks. |
L2 length | Optional light-chain CDR2 range for antibody frameworks. |
L3 length | Optional light-chain CDR3 range for antibody frameworks. |
At least one loop must be enabled. If a loop exists in the framework but is not listed in the design ranges, RFantibody keeps that loop fixed rather than redesigning it.
| Setting | Description |
|---|---|
Hotspot residues | Comma-separated antigen residues such as B146,B170,B177. These residues bias the model toward a particular epitope. Bad hotspot definitions can produce undocked designs, so small pilot runs are usually preferable before scaling up. |
| Output | Description |
|---|---|
| Designed complexes | Final antibody-antigen or nanobody-antigen complexes in PDB format. |
| File table | Downloadable list of all generated design files. |
| Score table | TSV summary exported from the final RF2 quiver output. |
RFantibody runs three design stages in sequence.
The first stage places a chosen framework against the target and redesigns the selected CDR loops. Rather than generating an arbitrary binder scaffold from scratch, this stage treats the framework as fixed context and focuses the generative step on loop-mediated docking and backbone creation around the target epitope.
Once loop backbones have been generated, ProteinMPNN samples amino acid sequences compatible with each designed structure. In RFantibody, this step is used to populate the redesigned loops while preserving the broader framework context.
The final stage predicts the structures of the designed sequences in complex with the target and scores whether the intended interface appears self-consistent. This filtering stage is important because antibody design campaigns generally require broad sampling, and only a subset of computational designs retain the desired dock after structure prediction.
RFantibody output is best treated as a ranked candidate set rather than a final answer. Structural inspection still matters: plausible designs should maintain a well-packed interface, avoid obvious clashes, and keep the framework geometry reasonable outside the redesigned loops.
The upstream guidance recommends filtering designs with strong RF2 confidence and low disagreement between the design model and the RF2-predicted complex. In practice, RF2 pAE below roughly 10 and design-versus-prediction RMSD below roughly 2 Å are used as minimal screening criteria before downstream experimental work or more detailed physics-based evaluation.
