Structure‐based design of a T‐cell receptor leads to nearly 100‐fold improvement in binding affinity for pepMHC
- 2 September 2008
- journal article
- research article
- Published by Wiley in Proteins-Structure Function and Bioinformatics
- Vol. 74 (4) , 948-960
- https://doi.org/10.1002/prot.22203
Abstract
T‐cell receptors (TCRs) are proteins that recognize peptides from foreign proteins bound to the major histocompatibility complex (MHC) on the surface of an antigen‐presenting cell. This interaction enables the T cells to initiate a cell‐mediated immune response to terminate cells displaying the foreign peptide on their MHC. Naturally occurring TCRs have high specificity but low affinity toward the peptide‐MHC (pepMHC) complex. This prevents the usage of solubilized TCRs for diagnosis and treatment of viral infections or cancers. Efforts to enhance the binding affinity of several TCRs have been reported in recent years, through randomized libraries and in vitro selection. However, there have been no reported efforts to enhance the affinity via structure‐based design, which allows more control and understanding of the mechanism of improvement. Here, we have applied structure‐based design to a human TCR to improve its pepMHC binding. Our design method evolved based on iterative steps of prediction, testing, and generating more predictions based on the new data. The final design function, named ZAFFI, has a correlation of 0.77 and average error of 0.35 kcal/mol with the binding free energies of 26 point mutations for this system that we measured by surface plasmon resonance (SPR). Applying the filter that we developed to remove nonbinding predictions, this correlation increases to 0.85, and the average error decreases to 0.3 kcal/mol. Using this algorithm, we predicted and tested several point mutations that improved binding, with one giving over sixfold binding improvement. Four of the point mutations that improved binding were then combined to give a mutant TCR that binds the pepMHC 99 times more strongly than the wild‐type TCR. Proteins 2009.Keywords
This publication has 46 references indexed in Scilit:
- Computational design of antibody-affinity improvement beyond in vivo maturationNature Biotechnology, 2007
- Structure-based Protocol for Identifying Mutations that Enhance Protein–Protein Binding AffinitiesJournal of Molecular Biology, 2007
- Computational Design of a New Hydrogen Bond Network and at Least a 300-fold Specificity Switch at a Protein−Protein InterfaceJournal of Molecular Biology, 2006
- Long-range cooperative binding effects in a T cell receptor variable domainProceedings of the National Academy of Sciences, 2006
- Affinity enhancement of an in vivo matured therapeutic antibody using structure‐based computational designProtein Science, 2006
- Directed evolution of human T cell receptor CDR2 residues by phage display dramatically enhances affinity for cognate peptide‐MHC without increasing apparent cross‐reactivityProtein Science, 2006
- Distance‐scaled, finite ideal‐gas reference state improves structure‐derived potentials of mean force for structure selection and stability predictionProtein Science, 2002
- The Protein Data BankNucleic Acids Research, 2000
- Application of Systematic Conformational Search to Protein ModelingMolecular Simulation, 1993
- CHARMM: A program for macromolecular energy, minimization, and dynamics calculationsJournal of Computational Chemistry, 1983