2019-01319 - PhD Position F/M 3D modeling of protein-RNA complexes by combinatorial assembly for protein design

Contract type : Public service fixed-term contract

Level of qualifications required : Graduate degree or equivalent

Fonction : PhD Position

Context

The PhD project is part of a multi-disciplinary European ITN project called RNAct, involving 8 inter-connected PhD projects in computational and experimental molecular biology, biophysics and system biology.

The overarching aim of RNAct is to integrate experiment and computation to design novel RNA-binding proteins, for synthetic biology and bio-analytics. RNAct will create and characterize novel functional RNA-Recognition motifs in proteins, with customized recognition of specific single-stranded RNA (ssRNA).

The CAPSID team is developing methods to model the 3D structure of biological macromolecules and their assemblages. Docking consists of modeling a molecular assembly from the 3D structure of each molecule, by sampling the possible relative positions of the two molecules, and evaluating the interaction energy to identify the most stable positioning . We have recently developed a method for modeling protein-bound RNAs by combinatorial assembly of fragments [see links 12, 3, 4, 5].

Assignment

Docking consist in 3D modeling of a molecular assembly from the structure of each constituent. The main limitation of classical docking methods is the flexibility of the molecules. Most proteins have limited and/or local flexibility, which can be neglected or modeled. Nucleic acids are more flexible and can radically change their conformation between their free forms and their protein-bound form. This makes docking based on known structures of the free form difficult, or even impossible in the case of single-stranded RNA.

We have developed a novel fragment-based method for docking a ssRNA of known sequence into a protein of known structure. The method consists in docking rigid ssRNA fragments extracted from known structures, and combinatorially assembling the docking poses with compatible sequence and position. The assembly of docking poses into chains corresponds to the search of lower energy path in a graph representing the pairwise connectivity of the poses. 

The current project aims at extending this method to incorporate more informations specific from proteins containing RNA-recognition motif, and apply it to protein design.

Main activities

The proposed PhD project focuses on the following main axis:

  • Optimize the algorithms for single-stranded RNA docking methodology. One optimisation step will be to switch from a brute force and exact search to a probabilistic search, by adding weights to the vertices and edges of the graph representing the pairwise connectivity of the docking  poses.
  • Automatise the method to create a RNA-protein 3D-model generation pipeline
  • Incorporate new sources of information for data-driven docking: multiple protein conformations, low resolution biophysical data (SAXS, cryo-EM, FRET), predicted amino-acid – nucleotide contacts by machin learning on sequence alignements...
  • Assist with developing a framework of protein design for RRMs

The PhD student will spend few months of secondments at Dynamic Biosensors GmbH (Germany) to relate in silico work to the experimental determination of RNA-RRM binding with biochips, and to learn about commercial software development.

Skills

The project is highly interdisciplinary: the day-to-day work involves a lot of programming on atomic representations of proteins and nucleic acids. Good proficiency in programming (preferentially Python and/or C++) and algorithmics are essential.

Knowledge of structural biology is very desirable but not mandatory, skills in discrete mathematics and statistics would be appreciated. Most importantly, candidates must be motivated to learn about all disciplines relevant to the project.

Candidates must be fluent either in French or in English.

Benefits package

  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
  • Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
  • Professional equipment available (videoconferencing, loan of computer equipment, etc.)
  • Social, cultural and sports events and activities
  • Access to vocational training
  • Social security coverage

Remuneration

Salary: 1982€ gross/month for 1st and 2nd year. 2085€ gross/month for 3rd year.

Monthly salary after taxes : around 1596,05€ for 1st and 2nd year. 1678,99€ for 3rd year. (medical insurance included).