First, the aptamer base sequences were taken from a previous SELEX study by . The UNAFold was used to get the 2D structure and .ct file . The .ct file was then used to get the dot-bracket notation of the sequence on the RNAStructure web server . In Dot-bracket notations, the base pairing is shown by matching opening and closing parentheses. Afterward, the tertiary structures were predicted and modeled using Vfold3D . Chimera , a molecular visualization tool, was then used to visualize the resulting 3D structures. After preparing the input files, the structures were uploaded for docking . The HDock software docks the aptamer to the TNF-α. The docking process began with default parameters to predict the binding modes of the aptamer to the receptor. Post-docking, the docking scores and the interaction analysis were used to recognize the most potential configuration. PyMOL was used to visualize the final binding modes for detailed interaction studies . GrASP is a graph neural network (GNN) that finds the binding site on the protein surface . Using this model, GrASP input graph entered into the GNN to predict the most druggable site of the receptor for the aptamers which processed the structural information to identify potential binding pockets. The TNF-α-aptamer interactions. The hydrophobic and hydrogen bond interactions formed between the amino acids and nucleotides are the driving force between their interactions.