Chuanhao Peng

The paper evaluates how glycan-binding proteins and immune cells recognize mirror-image glycans, finding widespread binding and donor-specific recognition of L-glycans.

The paper uses LiGA to profile glycan binding of gut bacteria, revealing cross-chiral recognition between natural bacteria and mirror-image glycans.

This paper develops MCNet, a machine learning model that predicts protein-glycan binding strength using atom-level representations, enabling cross-chiral recognition and unifying diverse glycobiology datasets.

This paper evaluates the multiplexed liquid glycan array (LiGA) for detecting ABO blood group antibodies in human serum, identifying its strengths and limitations.