ScanNet Protein Binding Site Prediction
A geometric deep learning model for predicting binding site probability from a structure.
Overview
A deep learning model for predicting protein-protein and protein-antibody binding sites using the spatio-chemical arrangements of atom and residue neighbors.
Run ScanNet Protein Binding Site Prediction on Neurosnap
The ScanNet Protein Binding Site Prediction online webserver allows anybody with a Neurosnap account to run and access ScanNet Protein Binding Site Prediction, no downloads required. Information submitted through this webserver is kept confidential and never sold to third parties as detailed by our strong Terms of Use and Privacy Policy.
Features
- 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.
Statistics
Neurosnap periodically calculates runtime statistics based on job execution data. These estimates provide a general guideline for how long your job may take, but actual runtimes can vary significantly depending on factors like input size or settings used.
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API Request
Access ScanNet Protein Binding Site Prediction using the Neurosnap API by sending a request using any programming language with HTTP support. To safely generate an API key, visit the API tab of your overview page.
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Citations
Please cite the original work when using ScanNet Protein Binding Site Prediction in publications or research outputs.
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Tubiana, J. et al. "ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction", https://nature.com, 30 May 2022, https://www.nature.com/articles/s41592-022-01490-7. |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |
Video Tutorial
The following youtube video describes how to use ScanNet Protein Binding Site Prediction using Neurosnap's online webserver. If you have any questions or want to suggest improvements for future tutorials please contact us here.