A computational algorithm to assess the physiochemical determinants of T cell receptor dissociation kinetics
A computational algorithm to assess the physiochemical determinants of T cell receptor dissociation kinetics
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.
- University of Chicago United States
- University of California, Davis United States
- University of California, San Francisco United States
Steered molecular dynamics, 1.1 Normal biological development and functioning, Applied Computing, Bioengineering, Steeredmoleculardynamics, Vaccine Related, Underpinning research, Information and Computing Sciences, Machine learning, Tcellreceptor, Peptide major histocompatibility complex, Numerical and Computational Mathematics, Machinelearning, Applied computing, Computation Theory and Mathematics, Biological Sciences, Immunogenicity, Biochemistry and cell biology, Biochemistry and Cell Biology, T cell receptor, Peptidemajorhistocompatibilitycomplex, TP248.13-248.65, Biotechnology, Research Article
Steered molecular dynamics, 1.1 Normal biological development and functioning, Applied Computing, Bioengineering, Steeredmoleculardynamics, Vaccine Related, Underpinning research, Information and Computing Sciences, Machine learning, Tcellreceptor, Peptide major histocompatibility complex, Numerical and Computational Mathematics, Machinelearning, Applied computing, Computation Theory and Mathematics, Biological Sciences, Immunogenicity, Biochemistry and cell biology, Biochemistry and Cell Biology, T cell receptor, Peptidemajorhistocompatibilitycomplex, TP248.13-248.65, Biotechnology, Research Article
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