Deeprank-GNN is a Graph Neural Network framework to learn interaction patterns from protein-protein interfaces
- See : Deeprank-GNN Github page
- See : Deeprank-GNN documentation
Shape-restrained protein-ligand HADDOCK docking
- See : P.I. Koukos, M.F. Reau and A.M.J.J. Bonvin. Shape-restrained modelling of protein-small molecule complexes with HADDOCK. bioRxiv doi:10.1101/2021.06.10.447890 (2021).
Early versions of this protocol were used to perform drug repurposing on COVID-19 proteins
Importance of inactive data in models : application to virtual screening in human health and environnement - example of nuclear receptors - Cnam, GBCM
This section summarizes my PhD work under the supervision of Pr Matthieu Montes.
Study of the evolution of the use of decoy compounds/ true inactive data in CADD benchmarking data sets.
Creation of the NR-DBIND (Nuclear Receptors DataBase Including Negative Data)
Identification of computer-aided drug design (CADD) pipelines to identify modulators of different nuclear receptors
- Docking approach
- Pharmacophore modeling approach
- See : Réau et al, Cells 2019
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The global objective of this project is to design and evaluate in vitro and in vivo theranostic small molecule inhibitors of TNFa to further provide inexpensive anti-TNFa therapies administered orally.
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Project coordinator : Pr Marc Port, Laboratoire de Chimie Moléculaire, CNAM
The project is supported by an ANR grant: Read the full ANR project
- Laboratoire CM (Chimie Moléculaire), CNAM, Paris
- Laboratoire GBA (Génomique, Bioinformatique et Applications), CNAM, Paris
- Laboratoire SATIE (Laboratoire des Systèmes et Applications des Technologies de l'Information et de l'Energie)
- PEPTINOV SAS