BiteNet

BiteNet is a computational approach for the large-scale detection of protein binding sites, that considers protein conformations as the 3D-images, binding sites as the objects on these images to detect, and conformational ensembles of proteins as the 3D-videos to analyze. Particularly, BiteNet is suitable for spatiotemporal detection of hard-to-spot allosteric binding sites.

If you use BiteNet please cite:

Kozlovskii, Igor, and Petr Popov. “Spatiotemporal identification of druggable binding sites using deep learning.”

BiteNet

  • Accepted file types: pdb.
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    The final model will be released once the manuscript will be peer-reviewed, revised, and published (it is peer-reviewed currently)