The paper introduces eSIG-Net, a novel interaction language model designed to predict how single missense mutations disrupt protein-protein interactions (PPIs). Unlike traditional tools that rely on static structures or basic sequences, this framework utilizes mutation-centric encoding and constrained discrepancy learning to identify subtle "interaction cliffs" where tiny genetic changes cause mas...去小宇宙查看完整单集简介
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