Research Areas
- Computational Biology
- Cancer Immunotherapy
- Cellular Immunity
- Therapy Design
Scientific Achievements
- Developed CrossDome and HLA-Arena 2.0, computational tools that make cancer immunotherapy safer by predicting risks to healthy cells
- Focused on personalized therapies, helping researchers identify the best targets for each patient’s tumor
- Led studies to improve immunotherapy safety and accessibility for patients from diverse ethnic backgrounds
Funding
RCMI Funding: U54MD015946 Pilot Grant
Other funding obtained with RCMI support: NIH/NCI R21CA289333 – Development of new computational environments for T- cell-based immunotherapies
Other funding obtained with RCMI support: NIH/NCI R21CA289333 – Development of new computational environments for T- cell-based immunotherapies
Scientific Advance
APE-Gen2.0: Expanding Rapid Class I Peptide–Major Histocompatibility Complex Modeling to Post-Translational Modifications and Noncanonical Peptide Geometries
Published in Journal of Chemical Information & Modeling, Volume 64, 2024, PMCID: PMC10936522.
Published in Journal of Chemical Information & Modeling, Volume 64, 2024, PMCID: PMC10936522.
This study describes the development of APE-Gen2.0, a new tool that improves prediction of how small peptides alert the immune system. Unlike earlier tools, APE-Gen2.0 can accurately model unusual cases such as peptides with post-translation chemical changes or non-standard binding. These features are important for identifying tumor-specific markers in cancer immunotherapy. The program increases modeling accuracy and helps researchers understand how chemical changes affect peptide binding strength. APE-Gen2.0 is available as a free, user-friendly web server, supporting broader use in immunology and cancer research.
NIH/NIMHD #U01CA258512 & CPRIT #RP170593
