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Integration of kinetic data into affinity-based models for improved T cell specificity prediction
Zahra S Ghoreyshi1, Hamid Teimouri2, Anatoly B Kolomeisky3
1Department of Biomedical Engineering, Texas A&M University, College Station, Texas; Center for Theoretical Biological Physics, Rice University, Houston, Texas.
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T cell receptor (TCR) and peptide-major histocompatibility complex (pMHC) interactions that result in T cell activation are complex and have been distinguished by their equilibrium affinity and kinetic profiles. While prior affinity-based models can successfully predict meaningful TCR-pMHC interactions in many cases, they occasionally fail at identifying TCR-pMHC interactions with low binding affinity. This study analyzes TCR-pMHC systems for which empirical kinetic and affinity data exist and prior affinity-based predictions have failed. We identify criteria for TCR-pMHC systems with available kinetic information where the introduction of a correction factor improves energy-based model predictions. This kinetic correction factor offers a means to refine existing models with additional data and offers molecular insights to help reconcile previously conflicting reports concerning the influence of TCR-pMHC binding kinetics and affinity on T cell activation.

