ProteinMPNN
Predict alternative sequences for an input protein structure with high accuracy. Also supports SolubleMPNN.
ProteinMPNN is a powerful inverse folding model that is capable of not only predicting the amino acids of a protein structure, but also certain chains, and complexes. Additionally, ProteinMPNN can be used as a way to create functional homologs / mutants of existing proteins by inverse folding their structures and sampling the sequence space.
Estimated resource cost: 0.0002945
Categories: Protein Design
Tags: Inverse Folding Proteins Solubility
Key Capabilities
- Predecessor to LigandMPNN. Note this service has been largely replaced by LigandMPNN and should no longer be used.
- Utilizes the faster & more feature rich ColabDesign implementation of ProteinMPNN.
- Supports SolubleMPNN.
- Allows you to specify fixed chains and positions.
- Allows you to inverse fold any protein or complex of proteins.
- Supports homo-oligomers.
- Supports different sampling techniques to better explore the protein landscape.
- Includes per sequence metrics such as an overall score and sequence recovery.
- Includes amino acid probabilities by position.
- Includes sampling temperature adjusted amino acid probabilities by position.
Runtime Statistics
| Metric | Value |
|---|---|
| runtime_mean | 35 |
| runtime_median | 19 |
| runtime_std | 85 |
| runtime_90th_percentile | 39 |
| runtime_max | 1265 |
Similar Tools
- LigandMPNN
- ABACUS-R Sequence Design
- BindFilter
- ESM-IF1
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: 0.0002945
Invite-only, limited-time access. Please contact ztang@getantibody.com.
Invite-only, limited-time access. Please contact ztang@getantibody.com.