Riley, Timothy P, Singh, Nishant K, Pierce, Brian G, Baker, Brian M, Weng, Zhiping, Timothy P. Riley, Nishant K. Singh, Brian G. Pierce, Brian M. Baker, Zhiping Weng
Editors
Barry L. Stoddard
Abstract
T-cell receptor (TCR) binding to peptide/MHC is key to antigen-specific cellular immunity, and there has been considerable interest in modulating TCR affinity and specificity for the development of therapeutics and imaging reagents. While in vitro engineering efforts using molecular evolution have yielded remarkable improvements in TCR affinity, such approaches do not offer structural control and can adversely affect receptor specificity, particularly if the attraction towards the MHC is enhanced independently of the peptide. Here we describe an approach to computational design that begins with structural information and offers the potential for more controlled manipulation of binding properties. Our design process models point mutations in selected regions of the TCR and ranks the resulting change in binding energy. Consideration is given to designing optimized scoring functions tuned to particular TCR-peptide/MHC interfaces. Validation of highly ranked predictions can be used to refine the modeling methodology and scoring functions, improving the design process. Our approach results in a strong correlation between predicted and measured changes in binding energy, as well as good agreement between modeled and experimental structures.
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 April 2016.
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#14,847,187
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#4,699
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