Generalizable mutation-effect prediction across adaptive immune recognition via unified multimodal framework

Abstract

Adaptive immunity is a central defence system essential for long-term and highly specific protection against pathogens through the precise molecular recognition of antigens by lymphocytes. However, predicting how mutations reshape these interactions remains a major challenge. Although previous computational approaches leverage large-scale pretraining for mutation-effect predictions, most are designed for specific tasks or modalities and struggle to generalize across the heterogeneous, multimodal landscape of immune recognition. Here we introduce UniAIR, a modular, multimodal framework for the accurate and generalizable prediction of mutation effects across immune recognition scenarios. UniAI..