Team, Visitors, External Collaborators
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Partnerships and Cooperations
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Section: Application Domains

Protein - Nucleic Acids Interactions

Participants : Isaure Chauvot de Beauchêne [contact person] , David Ritchie, Dominique Mias-Lucquin, Antoine Moniot, Honey Jain, Anna Kravchenko, Hrishikesh Dhondge, Malika Smaïl-Tabbone, Marie-Dominique Devignes.

The second application domain of Axis 2 concerns protein-nucleic acids interactions. We need to assess and optimize our new algorithms on concrete protein-nucleic acids complexes in close collaboration with external partners coming from the experimental field of structural biology. To facilitate such collaborations, we will have to create automated and re-usable protein-nucleic acid docking pipelines.

This is the case for our PEPS collaboration “InterANRIL” with the IMoPA lab (CNRS-Université de Lorraine). We are currently working with biologists to apply our fragment-based docking approach to model complexes of the long non-coding RNA (lncRNA) ANRIL with proteins and DNA. In order to extend this approach to partially structured RNA molecules, we have built an automated pipeline to create (i) libraries of RNA fragments with arbitrary characteristics such as secondary structure, and (ii) testing benchmarks for applying these libraries to docking assays.

In the framework of our LUE-FEDER CITRAM project (see above), we adapted this approach and this pipeline to single-strand DNA docking in order to model the complex formed by a bacterial relaxase and its target DNA.

In the future, we will tackle a defined group of RNA-binding proteins containing RNA-Recognition Motif (RRM) domains. We will study existing and predicted complexes between various types of RRMs and various RNA sequences with computational methods in order to calculate CG force-field energy and to help design new synthetic proteins with targeted RNA specificity. This is the goal of the ITN RNAct project and it will require the construction of a dedicated database equipped with querying and analysis facilities, including machine-learning approaches, as well as many interactions within the ITN RNAct consortium.