Biophysical Society Thematic Meeting - November 16-20, 2015

Biophysics in the Understanding, Diagnosis, and Treatment of Infectious Diseases Speaker Abstracts

High Resolution, High Throughput Structural Modeling of T Cell Receptor Specificity and Cross-Reactivity: Implications for Immunotherapy Timothy P. Riley 1 , Juan L. Mendoza 3 , Timothy T. Spear 2 , Michael I. Nishimura 2 , K. Christopher Garcia 3 , Brian M. Baker 1,2 . 1 University of Notre Dame, Notre Dame, IN, USA, 2 Loyola University Stritch School of Medicine, Chicago, IL, USA, 3 Stanford University School of Medicine, Stanford, CA, USA. T cell receptors (TCRs) recognize antigenic peptides bound and presented by class I or class II major histocompatibility complex proteins (peptide/MHC complexes). TCR recognition of a peptide/MHC complex defines specificity and reactivity in cellular immune responses. While structurally similar to antibody Fab fragments, there are key differences between TCRs and antibodies. Notably, TCRs do not undergo affinity maturation, and unlike mature antibodies, TCRs display a balance of specificity and cross-reactivity. Cross-reactivity is necessary given the limited size of the TCR repertoire relative to the universe of potential antigens, yet specificity is a fundamental feature of immunity. Many pathogens, particularly genetically unstable viruses, take advantage of TCR specificity for immune escape. In this context, there is increasing desire to engineer TCRs for therapeutic purposes. Design goals for engineered TCRs include efficient recognition of key antigens as well as known escape variants. Simultaneously, engineered TCRs must be biased against related self-antigens to avoid autoimmunity. The objective of this work is to develop the means to perform high resolution, high throughput modeling of TCR specificity and cross-reactivity in order to facilitate TCR targeting, identify cross-reactive antigens, and understand and combat immune escape. Our methodology combines large-scale experimental assessments of TCR cross-reactivity with computational modeling, structural biology, and biophysical analyses. Our results demonstrate the potential of this approach and highlight possible uses for the immunotherapy of genetically unstable viruses such as HCV and HIV, as well as other conditions with genomic instability.

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