FRSite: Protein drug binding site prediction based on faster R-CNN

Prediction of binding affinity of proteins and small molecules is a key step in drug design, and the location of binding sites is crucial for affinity prediction and molecular docking. In order to improve the accuracy of binding site prediction, a method called FRSite which improves the Faster R-CNN for protein binding site prediction is proposed in this paper. Multi-channel descriptors for proteins are generated to three dimensional (3D) girds and fed into the proposed Region Proposal Network (RPN-3D) network for potential proposals detection. Moreover, a 3D classifier is used to predict the bounding box of the binding site for a protein, and could also predict the center and size of the site. It can be seen from our comparative experiments that the proposed method can assist drug design.