MIF-ST
Predict alternative sequences for an input protein structure with high accuracy.
MIF-ST is a new and 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, MIF-ST can be used as a way to create functional homologs / mutants of existing proteins by inverse folding their structures and sampling the sequence space. Unlike other inverse folding models, MIF-ST also leverages sequence data in a novel way that allows it to accurately rank input sequences.
Estimated resource cost: 0.000248
Categories: Protein Design
Tags: Inverse Folding Proteins
Key Capabilities
- Allows you to inverse fold any protein.
- Excellent at predicting effects of mutations or variants.
- Includes per sequence metrics such as an overall score and sequence recovery.
- Supports different sampling methods and options.
Runtime Statistics
| Metric | Value |
|---|---|
| runtime_mean | 205 |
| runtime_median | 83 |
| runtime_std | 324 |
| runtime_90th_percentile | 524 |
| runtime_max | 1856 |
Similar Tools
- ABACUS-R Sequence Design
- ESM-IF1
- LigandMPNN
- ProteinMPNN
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: 0.000248
Invite-only, limited-time access. Please contact ztang@getantibody.com.
Invite-only, limited-time access. Please contact ztang@getantibody.com.