Dynamics of intrinsically disordered proteins: A concerted experimental and theoretical study
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|Dynamics of intrinsically disordered proteins: A concerted experimental and theoretical study
|Molecular motions play a central role for the properties of soft and biological matter. Intrinsically disordered proteins (IDPs) are fascinating biomolecules that have attracted recently a great interest in the scientific community. In contrast to normal proteins that have a well folded three-dimensional structure, IDPs are highly flexible biomolecules and populate a fluctuating conformational ensemble in solution. This large conformational plasticity is crucial for their biological function. IDPs share many physical properties with soft matter systems such as polymers or polyelectrolytes and from this perspective can be seen as living soft matter.
Neutron spectroscopy such as quasielastic neutron spectroscopy (QENS) and neutron spin-echo spectroscopy (NSE) provide an averaged view on the molecular motions of IDPs which is through very sensitive to changes of the environment of the molecules (e.g. the solvent) and to external stress (e.g. binding of a ligand or pressure). The essence of these changes are can be extracted by “minimalistic” models which are valid on long time scales and which have a clear physical interpretation. Preliminary studies show that the transition to the regime of asymptotic dynamics happens on a picosecond time scale, but this transition is not yet well understood. To gain more insight, the analytical modeling of QENS and NSE spectra can here be complemented by Molecular Dynamics simulations, using high performance computer (HPC) systems, which show conformational transitions on an atomistic level. On the other hand, these simulations can be used to compute neutron correlation functions which can be directly compared with the experimental QENS/ NSE data to validate the simulations.
In the suggested project the candidate will perform MD simulations on the HPC facilities that are available within FZJ and validate them with QENS/ NSE data. The modeling of experimental and simulation data will be performed in collaboration with CNRS, using existing software, as the nMoldyn package (Python/C), as well as Wolfram Mathematica code that will be further developed and implemented in Python, exploring in this context also concepts of machine learning.
In this way a unified theoretical framework for the dynamics of IDPs will be obtained and