Chapter title |
Computational Design of Ligand Binding Proteins
|
---|---|
Chapter number | 19 |
Book title |
Computational Design of Ligand Binding Proteins
|
Published in |
Methods in molecular biology, January 2016
|
DOI | 10.1007/978-1-4939-3569-7_19 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3567-3, 978-1-4939-3569-7
|
Authors |
Riley, Timothy P, Singh, Nishant K, Pierce, Brian G, Weng, Zhiping, Baker, Brian M, Timothy P. Riley, Nishant K. Singh, Brian G. Pierce, Zhiping Weng, Brian M. Baker |
Editors |
Barry L. Stoddard |
Abstract |
T-cell receptor (TCR) binding to peptide/MHC determines specificity and initiates signaling in antigen-specific cellular immune responses. Structures of TCR-pMHC complexes have provided enormous insight to cellular immune functions, permitted a rational understanding of processes such as pathogen escape, and led to the development of novel approaches for the design of vaccines and other therapeutics. As production, crystallization, and structure determination of TCR-pMHC complexes can be challenging, there is considerable interest in modeling new complexes. Here we describe a rapid approach to TCR-pMHC modeling that takes advantage of structural features conserved in known complexes, such as the restricted TCR binding site and the generally conserved diagonal docking mode. The approach relies on the powerful Rosetta suite and is implemented using the PyRosetta scripting environment. We show how the approach can recapitulate changes in TCR binding angles and other structural details, and highlight areas where careful evaluation of parameters is needed and alternative choices might be made. As TCRs are highly sensitive to subtle structural perturbations, there is room for improvement. Our method nonetheless generates high-quality models that can be foundational for structure-based hypotheses regarding TCR recognition. |
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