Titre de la dissertation: Deciphering sequence-controlled macromolecules – From sequence to 3D structures through modeling approaches

 Promoteur: Monsieur Mathieu Surin

Résumé de la dissertation

Sequence-controlled macromolecules (SCMs) are polymeric or oligomeric systems in which the sequence of monomers is partially or totally regulated. When the control is absolute, i.e. when all chains contain the exact same sequence and number of monomers, the material is classified as a sequence-defined macromolecule (SDM), a specific subclass of SCMs. SCMs are ubiquitous in Nature and perform specific biological functions, DNA and proteins being prime examples. Proteins, in particular, have the ability to fold into specific 3D structures, executing functions with very high selectivity and efficiency. This remarkable structural control is encoded in their sequence of monomers, the amino acids, which governs the folding process. The discovery of the importance of monomer sequence in natural macromolecules sparked a considerable interest among researchers, fuelling the desire to produce human-made SCMs. The recent advances in polymer synthesis have enabled the design of a wide range of fully synthetic SCMs, building on the virtually unlimited library of monomers available to a polymer chemist. However, this diversity of structures, while very attractive, brings considerable challenges: how to rationalize the design of synthetic SCMs? Which backbone and side-chains to use for a given application? What will be the 3D structure of the system in solution? Currently, synthetic SCMs are designed following “chemical intuition” rather than sound guidelines.

The aim of this thesis is to address these questions. The 3D structures of various natural and synthetic SCMs are investigated using the tools of molecular modelling. Molecular dynamics (MD) simulations, a computational method based on classical mechanics, allow us to predict the 3D structure and dynamics of (macro)molecular systems at the atomistic scale, using only their chemical structure as input. Our results are systematically compared to experimental data, to provide a better understanding of the links between sequence of monomers, 3D structure, and function.

The first part of the thesis focuses on biorecognition applications, one system targeting a protein, the other DNA. The simulations give insights on the mechanisms of assembly and the interactions at the molecular level, helping to understand experimental results.

The second part concerns the study of a supramolecular catalyst made by the assembly of two complementary SDMs, functionalized with nucleobases for the recognition between the chains, and catalytic units. MD simulations and network representations are used to elucidate the formation and dynamics of the catalytic duplex, and help to rationalize the experimental results of catalytic activity.

In the last part of the thesis, MD simulations are combined with small-angle X-ray scattering (SAXS) experiments to reveal the 3D structure of purely synthetic copolymers, in the context of single-chain polymeric nanoparticles. The folding in water is studied for two different copolymer designs, showing how the nature of the hydrophilic grafts can influence the resulting nanostructures.

Globally, our thesis provides insights into the sequence-structure-property relationships in SCMs, towards a rational design of functional macromolecular systems.