RFOptimization
Optimize an existing protein complex through RF3/Boltz-2 prediction and MPNN sequence-redesign cycles.
Overview
RFOptimization improves an existing biomolecular design through repeated sequence optimization and structure prediction. Each cycle uses RF3 gradient-guided optimization or Boltz-2 structure prediction, then ProteinMPNN or LigandMPNN redesigns the unfixed residues of protein chain A. Partner chains retain their sequences, and the redesigned complex seeds the next cycle. Review per-cycle confidence, RF3 optimization loss, redesigned sequences, and predicted structures.
Run RFOptimization on Neurosnap
The RFOptimization online webserver allows anybody with a Neurosnap account to run and access RFOptimization, no downloads required. Information submitted through this webserver is kept confidential and never sold to third parties as detailed by our strong Terms of Use and Privacy Policy.
Features
- Iterative optimization of an existing design complex with RF3 gradient optimization and Boltz-2 prediction.
- Mixed, RF3-only, and Boltz-2-only cycling strategies.
- Redesigns unfixed residues of chain A while preserving partner sequences.
- Preserves user-selected functional motifs throughout RF3 optimization and MPNN redesign.
- Supports global and per-position amino-acid exclusions during MPNN redesign.
- Supports protein, nucleic acid, and ligand partners, with LigandMPNN for ligand-aware sequence redesign.
- Exports per-cycle scores, redesigned sequences, predicted complexes, and the final optimized design.
Statistics
Neurosnap periodically calculates runtime statistics based on job execution data. These estimates provide a general guideline for how long your job may take, but actual runtimes can vary significantly depending on factors like input size or settings used.
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API Request
Access RFOptimization using the Neurosnap API by sending a request using any programming language with HTTP support. To safely generate an API key, visit the API tab of your overview page.
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Citations
Please cite the original work when using RFOptimization in publications or research outputs.
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Zhang, O., Wang, J., Thompson, T. R., You, Z., Song, Z., DiMaio, F., and Baker, D. RFOptimization: Guiding Design Optimization with All-Atom Structure Prediction. bioRxiv (2026). |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |