Development of a carbohydrate-binding protein prediction algorithm using structural features of stacking aromatic rings.

Carbohydrate-protein interactions play fundamental roles in numerous aspects of biological activities, and the search for new carbohydrate (CHO)-binding proteins (CBPs) has long been a research focus. In this study, through the analysis of CBP structures, we identified significant enrichment of aromatic residues in CHO-binding regions. We further summarized the structural features of these aromatic rings within the CHO-stacking region, namely "exposing" and "proximity" features, and developed a screening algorithm that can identify CHO-stacking Trp (tryptophan) residues based on these two features. Our Trp screening algorithm can achieve high accuracy in both CBP (specificity score 0.93) and CBS (Carbohydrate binding site, precision score 0.77) prediction using experimentally determined protein structures. We also applied our screening algorithm on AlphaGO pan-species predicted models and observed significant enrichment of carbohydrate-related functions in predicted CBP candidates across different species. Moreover, through carbohydrate arrays, we experimentally verified the CHO-binding ability of four candidate proteins, which further confirms the robustness of the algorithm. This study provides another perspective on proteome-wide CBP and CBS prediction. Our results not only help to reveal the structural mechanism of CHO-binding, but also provide a pan-species CBP dataset for future CHO-protein interaction exploration. [ABSTRACT FROM AUTHOR]