Protein sequence variants and catalytic activity measurements for miniaturized myoglobin scaffolds redesigned via deep learning. The collection documents structural modifications and their corresponding impact on enzymatic efficiency.
Use Cases
- Train models to predict catalytic enhancement using protein sequence features.
- Validate deep learning protein design outputs against experimental catalysis data.
- Analyze the relationship between miniaturized scaffold structure and enzymatic performance.
Strengths
- Focuses on miniaturized myoglobin protein scaffolds.
- Includes catalytic activity measurements for redesigned variants.
- Documents sequence modifications generated through deep learning-guided redesign.