Exploring the similarities of a large bank of protein pockets in a perspective of multiple protein-ligand interactions prediction

2024, Biology, diiP, Masters Internship

2024

Master’s Projects

@Biology

#Drug design in silico

#Protein pocket mining

#Ppocket druggability prediction

 

Project Summary

With the growing availability of data in the field of drug discovery, AI methods are promising for guiding and accelerating the search process for therapeutic molecules.

One challenge in drug design is to understand and predict the polypharmacology of molecules, i.e. their ability to interact with multiple protein targets.

We are developping an AI model to identify molecules capable of binding to a therapeutic target protein of interest but also to predict the proteins likely to bind the same molecules in order to prevent side effects or “off-targets”.

 

Anne-Claude Camproux
anne-claude.Camproux@u-paris.fr

  • Professor at Université Paris Cité

Lea Dufay

dufay.lea@gmail.com

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