Abstract Carbohydrate-binding modules (CBMs) are protein domains that typically reside near catalytic domains, increasing substrate-protein proximity by constraining the conformational space of carbohydrates. Due to the flexibility and variability of glycans, the molecular details of how these protein regions recognize their target molecules are not always fully understood. Computational methods, including molecular docking and molecular dynamics simulations, have been employed to investigate lectin-carbohydrate interactions. In this study, we introduce a novel approach that integrates multiple computational techniques to identify the critical amino acids involved in the interaction between a CBM located at the tip of bacteriophage J-1’s tail and its carbohydrate counterparts. Our results highlight three amino acids that play a significant role in binding, which we confirmed through in vitro experiments. By presenting this approach, we offer an intriguing alternative for pinpointing amino acids that contribute to protein-sugar interactions, leading to a more thorough comprehension of the molecular determinants of lectin-carbohydrate interactions.

Molecular Dynamics and Water site bias docking method allows the identification of key amino acids in the Carbohydrate Recognition Domain of a viral protein