Dynamic Protein Pattern Recognition in Free-Electron Laser Experiments

Supervisors: Prof. Sadia Bari (DESY), Prof. Robert Meißner (TUHH, Hereon)

Utilizing the unique pulsed features of x-ray free-electron laser (FELs), it will become possible not only to study the structure of radiation sensitive and fragile proteins as well as complexes, but also to gain a deeper understanding of their dynamics. Going beyond well-ordered systems, it is expected that the combination of x-ray scattering and x-ray spectroscopy methods combined with advanced molecular dynamics (MD) simulations will lead to real-time dynamics information about molecular migration and overall structural dynamics information of protein entities. Investigated mechanisms include folding-unfolding processes, protein aggregation or segregation as well as dynamics of intrinsically disordered proteins. Machine learning approaches, e.g. pattern recognition algorithms, will be used to identify energetically stable patterns in conformational space – allowing in combination with x-ray experiments deeper insights into the conformational space of proteins. Mathematical tools based on a probabilistic analysis of molecular motifs and kernel ridge regression techniques are used to determine the fingerprint of biomolecular conformations combining data from advanced MD simulations, online databases and x-ray spectroscopy data. This graduate school provides a unique opportunity to develop and optimize theoretical predictions and simulation algorithms utilizing the provided FEL and synchrotron-based spectroscopic data – from small peptides up to hierarchically built-up proteins.

Learn more in this short video.