Abstract 2356 Targeting Cancer peptide-MHC Neoantigens with de novo Designed Proteins

Major Histocompatibility Class I (MHC) Molecules serve as a window into the cell, whereby T-cells can use their T-cell receptor to recognize foreign peptides presented on the MHC of a cell and induce apoptosis. Unfortunately for diseases such as cancer, cancerous mutations may only be a single residue different from the native protein, resulting in similar mutant and wild-type peptide-MHCs. This small difference often results in negative selection of T-cell receptors that recognize mutant peptide-MHCs, leading to an absence of T-cells that can target cancer cells. This issue motivated us to use de novo protein design to generate binders with a high level of specificity between mutant and native peptide-MHCs. Using deep learning based protein design methods such as RFdiffusion and ProteinMPNN, we have generated promising in silico designs against a range of target peptides and MHC alleles. After selecting our top designs, we tested them using yeast surface display against our target MHC molecules with peptides loaded from KRas, PIK3CA, MAGE, and TP53 mutants. We observed binding events to all targets; some designs also had specificity to their respective mutant peptide-MHC over the wild-type peptide-MHC. After further work we have shown that the same design scaffold can bind to multiple peptide-MHC targets after slight redesign, similar to native T-cell receptors, holding promise that we could easily and quickly repurpose these scaffolds for new targets. Following these results we will incorporate our binders into T-cells as chimeric receptors and test for the ability of our binders to activate T-cell signaling and cell killing. This method of targeting peptide-MHC molecules is promising as a novel and rapid way to target cancer. This research has been made possible with help from my funding including the Washington Research Foundation Fellowship, the Mary Gates Research Scholarship, and the May Garrett Hayes Scholarship.