Axial attention includes column-wise and row-wise attention. More specifically, within the Axial attention module, the self-attention is first done along the vertical direction and then in the horizontal direction, corresponding to make attention along positions of protein atoms and ligand atoms individually. The specific network framework is shown in Fig. (Middle). Meanwhile, we also design a position encoding scheme in axial attention. Similar to the Graphormer model , we add row-wise attention related with 3D distance between pocket atoms and column-wise attention related with 3D distance between ligand atoms. The detailed model architecture is shown in Fig. (Right), where a row attention layer and column attention layer are arranged sequentially. The attention score A m ij denote the (i, j)-element of the Query-Key product matrix in the m-th row between atom pair h mi and h mj , we have: