A generalized framework for computational design and mutational scanning of T-cell receptor binding interfaces

Timothy P. Riley, Cory M. Ayres, Lance M. Hellman, Nishant K. Singh, Michael Cosiano, Jennifer M. Cimons, Michael J. Anderson, Kurt H Piepenbrink, Brian G. Pierce, Zhiping Weng, Brian M. Baker

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

T-cell receptors (TCRs) have emerged as a new class of therapeutics, most prominently for cancer where they are the key components of new cellular therapies as well as soluble biologics. Many studies have generated high affinity TCRs in order to enhance sensitivity. Recent outcomes, however, have suggested that fine manipulation of TCR binding, with an emphasis on specificity may be more valuable than large affinity increments. Structure-guided design is ideally suited for this role, and here we studied the generality of structure-guided design as applied to TCRs. We found that a previous approach, which successfully optimized the binding of a therapeutic TCR, had poor accuracy when applied to a broader set of TCR interfaces. We thus sought to develop a more general purpose TCR design framework. After assembling a large dataset of experimental data spanning multiple interfaces, we trained a new scoring function that accounted for unique features of each interface. Together with other improvements, such as explicit inclusion of molecular flexibility, this permitted the design new affinity-enhancing mutations in multiple TCRs, including those not used in training. Our approach also captured the impacts of mutations and substitutions in the peptide/MHC ligand, and recapitulated recent findings regarding TCR specificity, indicating utility in more general mutational scanning of TCR-pMHC interfaces.

Original languageEnglish (US)
Pages (from-to)595-606
Number of pages12
JournalProtein Engineering, Design and Selection
Volume29
Issue number12
DOIs
StatePublished - Jan 1 2016

Fingerprint

T-cells
T-Cell Antigen Receptor
Scanning
T-Cell Antigen Receptor Specificity
Mutation
Biological Products
Peptides
Therapeutics
Substitution reactions
Ligands

Keywords

  • Affinity
  • Mutational scanning
  • Specificity
  • Structure-guided design
  • T-cell receptor

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Biochemistry
  • Molecular Biology

Cite this

Riley, T. P., Ayres, C. M., Hellman, L. M., Singh, N. K., Cosiano, M., Cimons, J. M., ... Baker, B. M. (2016). A generalized framework for computational design and mutational scanning of T-cell receptor binding interfaces. Protein Engineering, Design and Selection, 29(12), 595-606. https://doi.org/10.1093/protein/gzw050

A generalized framework for computational design and mutational scanning of T-cell receptor binding interfaces. / Riley, Timothy P.; Ayres, Cory M.; Hellman, Lance M.; Singh, Nishant K.; Cosiano, Michael; Cimons, Jennifer M.; Anderson, Michael J.; Piepenbrink, Kurt H; Pierce, Brian G.; Weng, Zhiping; Baker, Brian M.

In: Protein Engineering, Design and Selection, Vol. 29, No. 12, 01.01.2016, p. 595-606.

Research output: Contribution to journalArticle

Riley, TP, Ayres, CM, Hellman, LM, Singh, NK, Cosiano, M, Cimons, JM, Anderson, MJ, Piepenbrink, KH, Pierce, BG, Weng, Z & Baker, BM 2016, 'A generalized framework for computational design and mutational scanning of T-cell receptor binding interfaces', Protein Engineering, Design and Selection, vol. 29, no. 12, pp. 595-606. https://doi.org/10.1093/protein/gzw050
Riley, Timothy P. ; Ayres, Cory M. ; Hellman, Lance M. ; Singh, Nishant K. ; Cosiano, Michael ; Cimons, Jennifer M. ; Anderson, Michael J. ; Piepenbrink, Kurt H ; Pierce, Brian G. ; Weng, Zhiping ; Baker, Brian M. / A generalized framework for computational design and mutational scanning of T-cell receptor binding interfaces. In: Protein Engineering, Design and Selection. 2016 ; Vol. 29, No. 12. pp. 595-606.
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