Using the Graph Attention Site Prediction (GrASP) website server, we applied graph neural networks (GNN) to verify the fact that the PROTAC attaching location is the druggable site . Graph Neural Networks (GNNs) are able to record the connections and interactions between nodes in a graph, in contrast to typical neural networks that process organized data such as scenes or images. The molecules are shown as graphs with bonds acting as edges and atoms as nodes. The probable drug binding site was then displayed, and the most important areas of the graph were highlighted by the attention mechanism. In Figure , the druggable region is displayed. This meant that the druggable site, which matched the EGF binding region in color, was displayed as yellow and green. This was further verified by predicting the druggable site (Figure ) employing P2Rank, a machine learning technology. The capacity to precisely target and bind medications to particular locations on proteins was symbolized by the term "druggable site." The process of creating therapies that can attach to these biomolecules requires the identification of druggable sites.