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Computational and Structural Biotechnology Journal
Article . 2022 . Peer-reviewed
License: CC BY NC ND
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PubMed Central
Other literature type . 2022
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A computational algorithm to assess the physiochemical determinants of T cell receptor dissociation kinetics

Authors: Rollins, Zachary A; Huang, Jun; Tagkopoulos, Ilias; Faller, Roland; George, Steven C;

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.

Country
United States
Keywords

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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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Average
Green
gold