On the intrinsic flexibility of the μ opioid receptor through multiscale modeling approaches

Thèse de l'étudiant: Doc typesDocteur en Sciences


G protein-coupled receptors (GPCRs) are one of the most important classes of therapeutic targets in the pharmaceutical industry. Recent releases of numerous GPCR X-ray crystal structures created the opportunity for computational methods to widely explore GPCR dynamics. GPCRs are indeed very flexible proteins that exhibit a large spectrum of conformations depending on the type of ligand, the oligomerization state, etc.

In our PhD thesis, we proposed to help understanding the biological implication of the intrinsic flexibility properties of μ opioid receptor (μOR), a key protein in the medical field as the target of most used anesthesia. To do so, we first performed classical all-atom (AA) Molecular Dynamics (MD) simulations of μOR in its apo form. We therefore highlighted that the various degrees of bendability of the α-helices present important consequences on the plasticity of the μOR binding site. Hence, this latter adopts a wide diversity of shape and volume during the MD simulations. Interestingly, some conformations of the binding site were closed to active-like conformations, indicating that basal activity of μOR is related to its flexibility properties. Such effect explains also why μOR can interact with diverse ligands presenting very different structural 3D geometries. Regarding the global conformational change of the μOR structure encountered during our simulations; a second important effect depicted a correlation between the motional modes of the extra- and intracellular parts of μOR on one hand, along with a clear rigidity of the central μOR domain on the other hand. Altogether, our results show how the modularity of the μOR flexibility and the plasticity of its binding site are related to its pre-ability to be activated, depicting atomistic structural information on the basal activity of μOR, one of its very important biological functions.

The second part of our PhD introduces a new strategy based on a set of in- house flexibility descriptors for parameterizing simple but precise coarse- grained (CG) elastic network models (ENMs) of μOR. Our CG models were validated by comparisons with the classical AA MD simulations of µOR. Optimized CG ENMs indeed reproduced in a high accurate way the flexibility properties of μOR as observed during the AA MD simulations, proving that the helical bendability of GPCRs can be efficiently studied with CG models.

In the last part of our work, one uses network modularization techniques to design so-called multi-grained (MG) models. They represent a novel type of low resolutions models. They are different in nature versus CG models as being true multi-resolution models, i.e., each MG interaction site grouping a different number of residues. MG models, despite their very low resolution, indeed reproduce in a high accurate way the dynamics obtained with the AA MD simulations. MG models are therefore useful for simulating the dynamics of µOR and other proteins at a domain or modular resolution.
la date de réponse20 janv. 2016
langue originaleAnglais
L'institution diplômante
  • Universite de Namur
SuperviseurDaniel Vercauteren (Promoteur), Aatto Laaksonen (Copromoteur), JOHAN WOUTERS (Président), Renaud Lambiotte (Jury), Raphaël Frédérick (Jury) & Mathieu Surin (Jury)

Attachement à un institut de recherche reconnus à l'UNAMUR

  • naXys

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