RFantibody
Generative antibody/nanobody design with fine-tuned RFdiffusion
Generate de-novo antibodies and nanobodies (VHHs) with atomic accuracy using RFantibody. This pipeline targets user-defined epitopes by leveraging fine-tuned RFdiffusion for backbone and docking prediction, ProteinMPNN for sequence optimization, and a specialized RoseTTAFold2 oracle to ensure structural validity and specificity.
Estimated resource cost: 0.000527
Categories: Protein Design
Tags: Antibodies Other Binders Proteins
Key Capabilities
- Epitope-guided de-novo CDR backbone generation and docking via fine-tuned RFdiffusion.
- ProteinMPNN-based sequence optimization tailored to the designed backbones.
- RoseTTAFold2 antibody oracle for structural self-consistency and off-target filtering.
Runtime Statistics
| Metric | Value |
|---|---|
| runtime_mean | 6127 |
| runtime_median | 1077 |
| runtime_std | 24636 |
| runtime_90th_percentile | 10172 |
| runtime_max | 377846 |
Similar Tools
- BindFilter
- BioPhi
- BioBind
- ProteinMPNN-ddG
Ready to submit your job?
Review your configuration, then confirm the estimated credit cost before you run the job. Note that credit estimates are not guaranteed and runtime can vary depending on inputs and settings.
Estimated Credits: 0.000527
Invite-only, limited-time access. Please contact ztang@getantibody.com.
Invite-only, limited-time access. Please contact ztang@getantibody.com.