ERC Consolidator Grant · 2024
Deep-learning for structure-based discovery of adaptive immune receptors
B- and T- cell adaptive immune receptor (AIR) repertoires are highly diverse, enabling response to a wide range of pathogens. While sequencing of an individual's immune repertoires is becoming common, our ability to convert these datasets into comprehensive antigen exposure information to inform clinical decisions is limited. The major challenges are to identify the antigens recognized by B-cell and T-cell immune receptors (BCRs/antibodies and TCRs), model their structures and determine their epitopes. Experimental approaches for epitope mapping are costly and low-throughput. While deep learning-based models have revolutionized structural biology by predicting highly accurate structures of…
From the public funding record at EU CORDIS. Describes the funded project, not the reviews below.