Doctoral student (M/F) in structural bioinformatics

Job Description

Thesis Subject

Despite the spectacular success of AI-based approaches for protein structure prediction, reliable 3D modeling of RNA remains a major challenge, mainly due to the limited number of experimentally resolved RNA structures. As a result, RNA—and in particular long non-coding RNAs (lncRNAs)—remains a largely underexploited therapeutic target, despite the central roles played by lncRNAs in several cancers.

This PhD project aims to establish an innovative pipeline combining chemical biology, biophysics, molecular modeling and artificial intelligence to enable structure-guided targeting of oncogenic lncRNAs. As a proof of concept, the project will focus on LENT, a lncRNA selectively expressed in melanoma, essential for tumor cell survival, and acting through the recruitment of the RNA helicase DHX36 to modulate the translation of mRNAs enriched in G-quadruplex motifs. Silencing of LENT induces apoptosis, highlighting its strong therapeutic potential.

The first objective is to obtain experimental structural constraints on LENT using RNA solution mapping approaches, which provide nucleotide-resolution information on lncRNA structure. These experimental constraints will then be used to guide deep learning-assisted RNA 3D structure prediction tools, in order to generate ensembles of structural models. Clustering and scoring steps will be used to identify the most representative conformations, which will subsequently be refined using intermediate-resolution cryo-EM maps to generate a consensus 3D model of LENT.

Finally, the refined structural models will serve as input for deep learning-based RNA–ligand prediction, using a dedicated RNA-focused chemical library. Predicted ligands will be experimentally validated using the state-of-the-art biophysical approaches available on our platform, including ITC microcalorimetry and grating-coupled interferometry, enabling a full characterization of the thermodynamic and kinetic parameters of RNA–ligand interactions. The identified compounds will then be tested in melanoma cells to assess their ability to interfere with LENT function and induce apoptosis; co-crystallization trials will also be undertaken to visualize RNA–ligand complexes.

Your Work Environment

The Ph.D. student (M/F) will work within the “RNA Architecture and Reactivity” unit and join the “Structure, Dynamics, and Targeting of Biomolecular Machines” team. This team currently consists of 6 researchers, 3 engineers, 1 postdoctoral fellow, and 2 Ph.D. students, and possesses extensive expertise in biochemistry, biophysics, and the structural biology of RNA. In particular, the team has easy access to the institute's biophysics platform, which is equipped for crystallization, the preparation of grids for electron microscopy, and studies of RNA-ligand interactions using biophysical approaches. The team also has dedicated computing resources (3D visualization workstations, GPU servers). The research will be conducted in close collaboration with Philippe Nghe's team (Laboratory of Structural Cell Biology at École Polytechnique). The laboratory is located on the university's central campus, easily accessible by public transportation. The candidate (M/F) will have access to a nearby university restaurant at a subsidized rate and will receive partial reimbursement for public transportation fares if necessary.

Constraints and risks

none

Compensation and benefits

Compensation

2300 € gross monthly

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

The research professions