Integration of Kinetic Data into Affinity-Driven Models for Improved T Cell-Antigen Specificity Prediction
Integration of Kinetic Data into Affinity-Driven Models for Improved T Cell-Antigen Specificity Prediction
Ghoreyshi, Z. S.; Teimouri, H.; Kolomeisky, A. T.; George, J. T.
AbstractT cell receptor (TCR) and peptide-major histocompatibility complex (pMHC) interactions that result in T cell activation are complex and have been identified 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 fail. We identify a 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.