| Summary: | B and T cells comprise the two major arms of the adaptive immune response tasked with clearing and preventing infection; molecular recognition in these cells occurs through antibodies and T cell receptors (TCRs), respectively. Highly successful therapeutics, clinical diagnostics and laboratory tools have been engineered from fragments of these parent molecules. The binding specificity, affinity and biophysical characteristics of these fragments determine their potential applications and resulting efficacies. Thus engineering desired properties into antibody and TCR fragments is a major concern of the multi-billion dollar biopharmaceutical industry. Toward this goal, we (1) designed antibody specificity using a novel computational method, (2) engineered thermoresistant Fabs by phage-based selection and (3) modulated binding kinetics for a single-chain TCR. In the first study, de novo modeling was used to generate libraries of FLAG peptide-binding single-chain antibodies. Phage-based screening identified a dominant design, and activity was confirmed after conversion to soluble Fab format. Bioinformatics analysis revealed potential areas for design process improvement. We present the first experimental validation of this in silico design method, which can be used to guide future antibody specificity engineering efforts. In the second study, the variable heavy chain of a moderately stable EE peptide-binding Fab was subjected to random mutagenesis, and variants were selected for resistance to heat inactivation. Thermoresistant clones where biophysically characterized, and structural analysis of selected mutations suggested general mechanisms of stabilization. Framework mutations conferring thermoresistance can be grafted to other antibodies in future Fab stabilization work. In the third study, TCR fragment binding kinetics for a clonotypic antibody were modulated by varying valence during phage-based selection. Binding affinity and kinetics for representative variants depended on the display format used during selection, and all TCR fragments retained binding to native pMHC antigen. This work demonstrates a general engineering platform for tuning protein-protein interactions. Using a combination of computational design and phage-based screening, we have identified antibodies and TCR fragments with improved binding properties or biophysical characteristics. The optimized variants possess a wider range of potential applications compared to their parent molecules, and we detail engineering methods likely to be useful in the engineering of many other protein-based therapeutics. === text
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