CoPo is a novel multimodal deep learning framework that integrates protein sequence, structure, and surface features to accurately predict covalent binding pockets.
By leveraging attention-based mechanisms, it provides interpretable, residue-level insights to facilitate covalent drug discovery across diverse targets, including those traditionally considered undruggable.