National Cancer Institute 3OT2CA297463-01S2

MATCHMAKERS - Creating and training AI tools for TCR binding prediction and design

This award funds the MATCHMAKERS project at MIT to develop AI tools for predicting and designing TCR binding to tumor antigens, combining machine learning with structural biology and immunology.

Description

Understanding how T cell receptors (TCRs) see tumor antigens presented by MHCs is necessary to fully understand how the immune system recognizes tumor antigens, and to reap the full potential of antigen-specific immunotherapy. To achieve this goal, a quantum leap forward is required in which the revolutionary advances in machine learning are combined with a large volume of structure, function, data on matched TCR-pMHC pairs. The development of accurate predictors of TCR-antigen recognition will be dependent on the creation and integration sequencing-based datasets with high-throughput structural and functional insights. Our proposal, submitted as a CRUK/NCI Grand Challenge team (MATCHMAKERS), will combine researchers with expertise in immunology, methods development, structural biology, and computation to enable generalized prediction and design of TCR recognition. This work will be spread across four Work Packages (WPs): WP1: Large-scale generation of TCR-pMHC pairs from naturally occurring sources. WP2: Ultra-high throughput TCR-pMHC matching using molecular engineering. WP3: Large-scale structural and biochemical analyses of TCR-pMHC interactions. WP4: AI-based prediction and design of TCR-pMHC interactions.

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