Computational Modeling of CXCR4 Receptor–Targeted CAR T-Cells for Medulloblastoma Therapy

Overview

Medulloblastoma is a fast-growing brain tumor that mostly affects children. Current treatments like chemotherapy and radiation can hurt healthy cells and cause bad side effects, sometime lead to death. CAR T-cell therapy is a new way to fight cancer by changing a patient's own immune cells (T-cells) to attack only cancer cells. The CXCR4 receptor is majorly observed on medulloblastoma cancer cells, so it could be a good target. We used industry standard tools like UniProt to get the amino acid sequence of CXCR4, AlphaFold3 to make a 3D model of the protein, and Protter to show it on the cell membrane. Then, we downloaded 3D structures of five different humanized antibodies from the Protein Data Bank (PDB codes: 8z3a, 8z39, 9c0u, 9c75, and 9e7g). Using the HDOCK server, we simulated how each antibody docks (binds) to CXCR4 (receptor). We did this three times for each antibody and averaged the results. Finally, PRODIGY calculated the binding energy-the lower (more negative) the number, the stronger the bind, meaning it will effectively destroy the cancer cell. All five antibodies bound to CXCR4 with negative energy, meaning they bind well. The antibody 8z39 had the strongest average binding energy, so it will work best for binding and destroying medulloblastoma cells. This project shows that computer modeling is a fast and safe way to test ideas for cancer treatments. It can help find the best antibodies quicker and cheaper than lab experiments alone. In the future, this could lead to enhanced CAR T-cell therapies for solid tumors like brain cancers/medulloblastoma.

Competition history

• CSEF 2026 Biochemistry/ Molecular Biology (Junior Division) · Entry J-04-20

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