Stage en bio-informatique et deep learning

Overview

Carbohydrates play essential biological roles as structural components, energy reservoirs, and mediators of molecular communication at the cell surface. Their diverse architectures enable precise recognition events that regulate immunity, development, and host–pathogen interactions. As a result, protein–carbohydrate contacts influence processes ranging from tumor progression to viral and bacterial infection, making carbohydrates and their binding proteins valuable targets for therapeutic design. However, comparing protein–carbohydrate interfaces remains challenging due to carbohydrate diversity, ligand flexibility, and experimental limitations.

In 2024 our group released the DIONYSUS database, gathering carbohydrate-containing structures annotated with available general and carbohydrate-specific information on both proteins and ligands. Clustering of non-covalent carbohydrate binding sites according to their 3D geometry revealed missing functional annotations in state-of-the-art curated databases.

In its current state, DIONYSUS provides an integrated, user-friendly platform for exploring binding-site similarities, carbohydrate specificity, and complex quality, offering a robust foundation for comparative analysis of carbohydrate-binding sites and strong potential for the development of deep learning methods for prediction of protein–carbohydrate interactions.

Responsibilities

• Development of protein–carbohydrate prediction tools using advanced deep learning techniques such as diffusion models.
• Enrichment of DIONYSUS annotations by including protein and carbohydrate flexibility information using databases such as GlycoShape and GlycoShield, and by performing molecular dynamics simulations.
• Evaluation of the performance of state-of-the-art tools modelling protein–ligand interactions (e.g., AlphaFold3 and Boltz-2) on the task of modelling protein–carbohydrate interactions.

Qualifications

• Proficient in Python, in particular with scikit-learn and PyTorch.
• Experience in machine learning model development and applications.
• Familiarity with basic structural bioinformatics concepts.

References

Gheeraert A, Bailly T, Ren Y, Hamraoui A, Te J, Vander Meersche Y, Cretin G, Leon Foun Lin R, Gelly J-C, Pérez S, Guyon Frédéric & Galochkina T. DIONYSUS: a database of protein-carbohydrate interfaces. Nucleic Acids Res 53(D1), D387-D ). DOI: /nar/gkae890

Gheeraert A, Guyon F, Pérez S, Galochkina T. Unraveling the diversity of protein-carbohydrate interfaces: insights from a multi-scale study. Carbohydr Res, ). DOI: /j.carres.