New article in Computational and Structural Biotechnology Journal

A new publication from collaborators and Dr. Ilias Tagkopoulos, about A Computational Algorithm to Assess the Physiochemical Determinants of T Cell Receptor Dissociation Kinetics.

Abstract: The rational design of T Cell Receptors (TCRs) for immunotherapy has stagnated due to a limited understanding of the dynamic physiochemical features of the TCR that elicit an immunogenic response. The physiochemical features of the TCR-peptide major histocompatibility complex (pMHC) bond dictate bond lifetime which, in turn, correlates with immunogenicity. Here, we: i) characterize the force-dependent dissociation kinetics of the bond between a TCR and a set of pMHC ligands using Steered Molecular Dynamics (SMD); and ii) implement a machine learning algorithm to identify which physiochemical features of the TCR govern dissociation kinetics. Our results demonstrate that the total number of hydrogen bonds between the CDR2β-MHC⍺(β), CDR1α-Peptide, and CDR3β-Peptide are critical features that determine bond lifetime.

Reference: Rollins, Zachary A., Jun Huang, Ilias Tagkopoulos, Roland Faller, Steven C. George. “A computational algorithm to assess the physiochemical determinants of T cell receptor dissociation kinetics.” Computational and Structural Biotechnology Journal (2022). doi: 10.1016/j.csbj.2022.06.048 (link)