Melyssa Cheung

Benchmarking AlphaFold and related deep learning approaches for modeling antibody and TCR antigen recognition

This study benchmarks AlphaFold and related methods for modeling antibody and TCR antigen recognition, showing improvements with AlphaFold3 and increased sampling but varying success across complex types.

Dynamic S-acylation of GSDMA regulates pyroptosis

This study shows that GSDMA undergoes S-acylation, which promotes pyroptosis by enhancing membrane anchoring and oligomerization, distinct from GSDMD's palmitoylation mechanism.

Structural characterization and AlphaFold modeling of human T cell receptor recognition of NRAS cancer neoantigens

The paper determines crystal structures of a TCR complex with NRAS neoantigens and uses AlphaFold to model these complexes, showing varying success across different implementations.

Exploring the Potential of Structure-Based Deep Learning Approaches for T cell Receptor Design

This study evaluates two deep learning methods for designing T cell receptors by comparing their performance to physics-based approaches in binding target antigens.