| Description |
The search for new drugs and materials based on peptides or oligopeptides is at the forefront of pharmaceutical research. Knowledge of the structure of these systems is essential for optimizing their physicochemical properties and actual therapeutic application, but determining the structure of these solids, which mostly exist in microcrystalline, semicrystalline and amorphous states, is difficult if not impossible. Advanced NMR crystallography and structure prediction methods using quantum-mechanical approaches, machine learning and large-scale NMR parameter predictions are now bringing new opportunities in this area. All of these methods can be considered complementary in that they describe the solid-state structure independently. However, each has its own specific limitations. The aim of this PhD project is to develop and test a methodology for solving complex structures of peptides and oligopeptides in their crystalline and amorphous states based on a combination of experimental ss-NMR spectroscopy and large-scale structure prediction. |
