The chemoinformatics and proteochemometrics group is dedicated to the identification of pharmacological modulators of macromolecular interactions such as protein-protein interactions (PPI) by small molecules using in silico approaches. It combines chemoinformatics and structural bioinformatics techniques to characterize the structural properties of binding cavities present at the core of PPI interfaces and the most suitable physicochemical profile of the small molecules meant to modulate them. An important aspect of our work relies on the rationalization of the chemical space of protein-protein interactions’ inhibitors by analyzing the properties of successful examples of pharmacological PPI modulations. To this end, we are driving the iPPI-DB initiative project (http://ippidb.pasteur.fr/), a database of PPI modulators (only small molecules). This database is a great source of pharmacological data that help us to derive some trends about the PPI chemical space using machine learning techniques. Another aspect of our project is also to get some insight into the PPI interfaces’ properties themselves that obviously condition the binding of small compounds. To this end, we are mapping the whole PPI pocketome in order to assess the ligandability of all binding pockets present within PPIs. By crossing both types of information, i.e by crossing the target and the chemical spaces of PPIs, we aim at determining which chemotypes should be associated with which types of PPI targets. The final goal is therefore to facilitate the identification of quality chemical probes on PPI targets and more generally on macromolecular interactions by the mean of complementing chemical biology approaches. This expertise is used to design chemical libraries using chemoinformatics approaches that are tuned to specific projects and that can be employed to do either virtual ligand screening (VLS) within the team, or high throughput screening (HTS) campaigns.
Protein-Protein Interactions (PPIs) are involved in most biological process and diseases. With a recently estimated number of 370,000 PPIs in humans, they constitute a large ‘reservoir’ for therapeutic development compared to ‘conventional’ drug targets. […]
A common phenomenon in most microbial infections is the attenuation of the host’s immediate immune response, allowing for long-term colonization. We and others have shown that many pathogens achieve this by manipulating the epigenetic […]
Design of Antiviral drugs for Bronchiolitis Virus using a novel therapeutic target.
Drug Discovery & Screening at Institut Pasteur
The Technological Targeted Action Drug Discovery and Screening (ATC-DDS) coordinates projects and collaborations at the Institut Pasteur Paris campus on therapeutic development. It raises awareness for DDS in basic research projects and stimulates intra-campus […]
In order to boost the identification of low-molecular-weight drugs on protein-protein interactions (PPI), it is essential to properly collect and annotate experimental data about successful examples. This provides the scientific community with the necessary […]
2022Characterization of the Interaction Domains between the Phosphoprotein and the Nucleoprotein of Human Metapneumovirus., J Virol 2022 01; 96(2): e0090921.
2021InDeep: 3D fully convolutional neural networks to assist in silico drug design on protein-protein interactions., Bioinformatics 2021 Dec; (): .
2021Phylogenetic analysis of Harmonin homology domains., BMC Bioinformatics 2021 Apr; 22(1): 190.
2021New machine learning and physics-based scoring functions for drug discovery., Sci Rep 2021 Feb; 11(1): 3198.
2021The iPPI-DB initiative: A Community-centered database of Protein-Protein Interaction modulators., Bioinformatics 2021 Jan; (): .
2020Fr-PPIChem: An academic compound library dedicated to protein-protein interactions, ACS Chem. Biol. 2020 Apr;.
2017Privileged Substructures to Modulate Protein-Protein Interactions, J Chem Inf Model 2017 Oct;57(10):2448-2462.
2016Imbalance in chemical space: How to facilitate the identification of protein-protein interaction inhibitors, Sci Rep 2016 Apr;6:23815.
2015Sampling of conformational ensemble for virtual screening using molecular dynamics simulations and normal mode analysis, Future Med Chem 2015;7(17):2317-31.
2015A Proteometric Analysis of Human Kinome: Insight into Discriminant Conformation-dependent Residues, ACS Chem. Biol. 2015 Dec;10(12):2827-40.
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