2024

Master’s Projects

@Biology

#Transformers network finetuning

#Structural bioinformatics

#Protein/peptide prediction interaction

#Knottin

 

Project Summary

The Project explores the design of protein knottins to target P-selectin and integrins involved in vaso-occlusive crises in sickle cell disease (SCD). Leveraging advanced AI technologies such as AlphaFold2, AlphaFold3, RFdiffusion, and ProteinMPNN, integrins αMβ2, α4β1, αLβ2, αVβ3, and P-selectin were modeled. These deep learning tools enabled the engineering of knottins to block pathological cell adhesion interactions. The use of AI and deep learning led to promising candidates, particularly for binding the Mac-1 integrin. Further experimental validation is needed to confirm these findings, potentially leading to novel, effective therapeutic approaches for SCD.

 

Jean-Christophe Gelly
jean-christophe.gelly@u-paris.fr

Professor at Université Paris Cité

Biologie Intégrée du Globule Rouge
INSERM UMR_S1134 – Université Paris Cité
Hôpital Necker APHP | Bâtiment Lavoisier
149 Rue de Sèvres, 75015 Paris

Azouzi Slim

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