Unraveling the diversity of protein-carbohydrate interfaces: insights from a multi-scale study
Aria GheeraertiD, Frédéric GuyoniD, Serge PéreziD, Tatiana V. GalochkinaiD
Abstract
Protein-carbohydrate interactions play a crucial role in numerous fundamental biological processes. Thus, description and comparison of the carbohydrate binding site (CBS) architecture is of great importance for understanding of the underlying biological mechanisms. However, traditional approaches for carbohydrate-binding protein analysis and annotation rely primarily on the sequence-based methods applied to specific protein classes. The recently released DIONYSUS database aims to fill this gap by providing tools for CBS comparison at different levels: both in terms of protein properties and classification, as well as in terms of atomistic CBS organization. In the current study, we explore DIONYSUS content using a combination of the suggested approaches in order to evaluate the diversity of the currently resolved non-covalent protein-carbohydrate interfaces at different scales. Notably, our analysis reveals evolutionary convergence of CBS in proteins with distinct folds and coming from organisms across different kingdoms of life. Furthermore, we demonstrate that a CBS structure based approach has the potential to facilitate functional annotation for the proteins with missing information in the existing databases. In particular, it provides reliable information for numerous carbohydrate-binding proteins from rapidly evolving organisms, whose analysis is particularly challenging for classical sequence-based methods.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 2
- FWCI
- 0.60
- Field percentile
- top 44%
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Structure-Based Neural Network Protein-Carbohydrate Interaction Predictions at the Residue Level
S. W. Canner, S. Shanker, J. J. Gray·bioRxiv·Mar 14, 2023
- Predictions from Deep Learning Propose Substantial Protein-Carbohydrate Interplay
Samuel W. Canner, Ronald L. Schnaar, Jeffrey J. Gray·Proceedings of the National Academy of SciencesPeer-reviewed·May 18, 2026
- Prediction of protein-carbohydrate binding sites from protein primary sequence
Md Muhaiminul Islam Nafi, Quazi Farah Nawar, … Mohammad Saifur Rahman·bioRxiv·Feb 9, 2024
- Evaluation of De Novo Deep Learning Models on the Protein-Sugar Interactome
Samuel W. Canner, Lei Lü, … Jeffrey J. Gray·bioRxiv·Sep 2, 2025
- Boosting the analysis of protein interfaces with Multiple Interface String Alignment: illustration on the spikes of coronaviruses
S. Bereux, Bernard Delmas, Frédéric Cazals·Proteins Structure Function and BioinformaticsPeer-reviewed·Nov 15, 2021
- CLIMBS: assessing carbohydrate-protein interactions through a graph neural network classifier using synthetic negative data
Yijie Luo, Fabio Parmeggiani·Journal of Chemical Information and ModelingPeer-reviewed·Apr 3, 2026