Felix Kümmerer: Integrating molecular simulations and biophysical experiments to study structure and dynamics of biomolecules Date: 01-02-2023    Supervisor: Kresten Lindorff-Larsen

The structure and dynamics of biomolecules such as proteins and RNA are critical to their function, stability, and ability to interact with their environment. Malfunctioning proteins are the cause of many diseases and understanding them in a structural context is crucial for the design of drugs that target them. Meanwhile, proteins and RNA are themselves common drugs and vaccines, with growing applications in biotechnology, energy, and many other important fields.

Biophysical experiments can provide fundamental and accurate insights into these properties, but the results obtained are often difficult to interpret. Molecular simulations, on the other hand, can provide a molecular model at spatial resolution and time scales that are challenging to probe experimentally. However, molecular simulations are only approximations of nature and can therefore be inaccurate, making it crucial to validate them. A common approach is thus to combine simulations and experiments. These approaches, known as integrative structural modelling, combine the accuracy of experiments with the detailed insights provided by molecular simulations to help us understand biological problems.

This thesis deals with the development and application of different frameworks in the context of integrative structural modelling, with particular emphasis on integrating experimental data directly with simulations. One focus is on the interpretation of time-dependent data obtained from NMR experiments, which provide information on the fast dynamics of proteins. This is achieved through the development and application of a reweighting method to fit experimental data using molecular simulations. The thesis also highlights the limitations of such integrative approaches and shows how these insights can be used to optimise the models underlying the simulations. Finally, an additional approach is presented that demonstrates the benefits of using integrative modelling in RNA structure determination using an extensive set of NMR data in combination with molecular simulations.