SaProt_650M_AF2
| Property | Value |
|---|---|
| License | MIT |
| Framework | PyTorch |
| Downloads | 19,777 |
| Task Type | Fill-Mask, Protein Analysis |
What is SaProt_650M_AF2?
SaProt_650M_AF2 is an advanced protein language model designed to work with AlphaFold2 structure predictions. It specializes in masked sequence prediction and mutation effect analysis, incorporating structural information through pLDDT scores. The model can be utilized through both Hugging Face transformers and ESM frameworks, offering flexibility in implementation.
Implementation Details
The model implements a transformer architecture and provides two distinct interfaces for usage. It can process protein sequences with structural confidence annotations (marked by '#' for low pLDDT regions) and outputs predictions in various formats including mutation effects and amino acid probabilities.
- Dual interface support (Hugging Face and ESM)
- Built-in mutation effect prediction capabilities
- Protein embedding generation functionality
- Structure-aware sequence processing
Core Capabilities
- Masked protein sequence prediction
- Mutation effect analysis and scoring
- Position-specific amino acid probability prediction
- Protein embedding generation
- Integration with AlphaFold2 structural confidence scores
Frequently Asked Questions
Q: What makes this model unique?
The model's ability to incorporate structural confidence information from AlphaFold2 predictions makes it particularly powerful for protein sequence analysis. It can process sequences with explicit marking of low-confidence regions, enabling more accurate predictions.
Q: What are the recommended use cases?
The model is ideal for protein engineering applications, including mutation effect prediction, protein sequence analysis, and generating protein embeddings for downstream tasks. It's particularly useful when working with AlphaFold2-predicted structures and analyzing their reliability.
