Computational Design of a TCR-Based Bispecific Engager Targeting Cancerous KRAS G12V Mutations.

Area of Science:

• Immunotherapy
• Computational Biology
• Oncology

Background:

• Bispecific T-cell engager (BiTE) therapy redirects cytotoxic T cells to target cancer cells by binding CD3 on T cells and tumor-specific antigens.
• Traditional BiTEs face off-tumor effects due to targeting cell surface antigens not exclusive to certain cancer types.
• KRAS G12V mutations are common in various cancers but lack FDA-approved targeted therapies.

Purpose of the Study:

• To computationally design novel T-cell receptor-bispecific T-cell engagers (TCR-BiTEs) targeting the KRAS G12V neoantigen.
• To explore the potential of computational methods in designing immunotherapies for mutations lacking targeted treatments.
• To develop TCR-BiTEs specific to KRAS G12V presented by different HLA types (HLA:03:01 and HLA:11:01).

Main Methods:

• Utilized a computational approach to design TCR-BiTE structures.
• Incorporated a T-cell receptor (TCR) for specific binding to the KRAS G12V neoantigen.
• Employed AlphaFold tools, free energy estimation, and molecular dynamics analysis for structural validation.

Main Results:

• Successfully designed two TCR-BiTE structures targeting KRAS G12V for specific HLA types (HLA:03:01 and HLA:11:01).
• Validated the computational design of the TCR-BiTE structures using advanced computational tools.
• Established a potential computational pipeline for designing TCR-BiTEs against other mutations.

Conclusions:

• The designed TCR-BiTEs represent promising starting points for in vitro evaluation and further development.
• Computational design offers a viable strategy for creating targeted immunotherapies for KRAS G12V and other mutations.
• This study highlights the underdeveloped potential of computational approaches in immunotherapy design.