Design of high specificity binders for peptide-MHC-I complexes

Area of Science:

• Immunology
• Structural Biology
• Computational Biology

Background:

• Class I Major Histocompatibility Complex (MHC) molecules present intracellular peptides on cell surfaces for immune surveillance.
• Targeting peptide-MHC (pMHC) complexes offers therapeutic potential but faces challenges due to limited peptide epitopes and ubiquitous MHC expression.

Purpose of the Study:

• To develop *denovo* designed small proteins capable of specifically targeting pMHC complexes.
• To create binders that interact primarily with the peptide antigen, minimizing off-target binding to the MHC molecule.

Main Methods:

• Utilized deep learning-based protein design tools to engineer novel small proteins.
• Designed proteins to specifically bind to ten distinct target pMHC complexes.
• Displayed designed binders on yeast for binding assays and incorporated them into chimeric antigen receptors (CARs) for T-cell activation studies.

Main Results:

• Identified specific binders for ten target pMHCs, demonstrating high specificity against closely related peptides.
• Engineered CARs incorporating five of the designed binders, leading to significant T-cell activation against cognate pMHC complexes.
• Achieved T-cell activation levels substantially above background noise from non-cognate peptide-MHC complexes.

Conclusions:

• Deep learning *denovo* protein design can generate highly specific binders for pMHC complexes.
• This approach enables precise targeting of pMHCs for potential therapeutic interventions.
• The method is adaptable for use with experimental or predicted pMHC structures, offering broad applicability in protein and cell-based targeting strategies.