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.

This paper develops a phage-based liquid lectin array to detect subtle glycocalyx differences by displaying multivalent lectins on DNA-barcoded M13 phage.