Initially, the 3D structure of the IL-13Rα2 receptor was predicted using the AlphaFold 3 program . The antibodies obtained for this research were downloaded from the protein data bank. In the next step, the antibodies were docked to the IL-13Rα2 by uploading the input files into the HDOCK2.4 software . Using the docking scores and other outputted analyses, the most likely occurrence was determined from the resulting confirmations . The most druggable/binding sites were then outputted using a graph neural network (GNN) program called GrASP . GNNs use data structures of objects and their relationships to power their outputted predictions, and GrASP works by utilizing a GNN model designed explicitly for druggable site prediction. While processing the input graph, the GNN model examined structural information, allowing GrASP to predict the receptor's most druggable site for the aptamers. The IL-13Rα2-antibody hydrogen bond interactions were computed using an in-house script. The binding energy between the IL-13Rα2 receptor and antibodies was obtained using PRODIGY software .