Joint fusion of sequences and structures of drugs and targets for identifying targets based on intra and inter cross-attention mechanisms

Experimental results show that despite our benchmark dataset being one-third or the same size of those used by current state-of-the-art methods, MM-IDTarget achieves the performance on par with or superior to these methods across most Top-K evaluation metrics based on the same test set for targets identification. Moreover, MM-IDTarget exhibits the strong application capability on two generalization datasets and one dataset constructed from approved drugs, establishing it as a robust tool for targets identification.