Before a T cell can recognize an antigen, that antigen must be processed and presented as a
peptide on an MHC molecule. Modeling this antigen processing pathway lets us predict which
peptides become CD4+ T-cell epitopes, yet the underlying biophysical computations are
expensive. This project makes epitope prediction practical by accelerating the core
calculations on the GPU and packaging them into an easy-to-use suite.
Faster conformational stability
CD4+ epitope prediction depends on conformational stability calculations that dominate the
runtime. We re-engineered this computation for the GPU and achieved large speedups:
Accelerated sampling
The same pipeline relies on Markov Chain Monte Carlo sampling. We built a GPU
implementation that delivers substantial gains over the CPU baseline:
An integrated suite
Finally, we packaged antigen processing likelihood and epitope prediction into a single
application so others can run the full workflow end to end:
All related publications are listed below.
Related Publications
This post is written by Jiarui Li, licensed under CC BY-NC 4.0.