ScanNet Protein Binding Site Prediction
A geometric deep learning model for predicting binding site probability from a structure.
A deep learning model for predicting protein-protein and protein-antibody binding sites using the spatio-chemical arrangements of atom and residue neighbors.
Estimated resource cost: 0.000248
Categories: Molecular Docking & Interactions
Tags: Antibodies Binding Site Prediction Proteins
Key Capabilities
- Predict probabilities of functional sites.
- Uses 3-dimensional protein structures to detect protein-protein and protein-antibody binding sites.
- Displays a sequential view of residue-level binding site probabilities and an exportable chart of the probabilities.
Runtime Statistics
| Metric | Value |
|---|---|
| runtime_mean | 21 |
| runtime_median | 20 |
| runtime_std | 6 |
| runtime_90th_percentile | 26 |
| runtime_max | 106 |
Similar Tools
- AF2Bind
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- ColabDock
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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.