SimTech projects and third-party funding
We develop a physics-informed machine learning framework for the reverse transformation of coarse-grained macromolecules to atomistic detail. By using modern machine learning techniques and incorporating physical and chemical knowledge, the backmapping process will be accelerated and the accuracy will be increased compared to state-of-the-art algorithms. The final python package will be made available to the community following the FAIR (Fair, Accessible, Interoperable, and Reusable) principles.
Researchers: Birgit Hillebrecht, Christian Pfaendner
Further information: Artificial intelligence meets molecular dynamics: certified machine learning for resolution transformation
We aim to improve biological molecular dynamics (MD) simulations by (i) establishing force field parameters of diverse post-translational modifications (PTM) and investigating their roles, (ii) extending constant pH MD simulations by titratable PTMs, and (iii) developing a novel resolution conversion method based on machine learning.
Researcher: Viktoria Korn
Further information: Biological Molecular Dynamics Simulations 2.0
In this project the coarse-grained structures and force field parameters of metal-organic frameworks (MOFs) with functionalized linkers of varying length will be developed. Molecular Dynamics simulations of the functionalized MOFs will be performed to evaluate the optimal linker lengths for certain organocatalytic reactions. The swelling of the MOFs caused by different solvents, temperatures and linker lengths will be simulated to understand the spatial restrictions upon pore deformation. The isoreticular MOF series will allow us to predict the optimal transport/confinement ratio for specific reactant/catalyst/product combinations. To investigate the molecular transport in dynamic MOFs, the simulation of the repeated scaffold contraction and expansion will give an initial estimate of the optimal switching speed for the individual MOFs.
Researcher: Sofia Kolin
Further information: Dynamic confinement in soft porous crystals
Gasdermins are a family of proteins that facilitate pyroptosis, a defense mechanism against infections, by forming medium-sized pores in membrane bilayers. However, the initiation of the gasdermin pore formation remains a mystery. Using extensive molecular dynamics (MD) simulations, we are investigating the insertion and excision of gasdermin-A3.
Researcher: Viktoria Korn
We investigate the interactions among the transmembrane domains of BCL-2 receptors in mitochondrial outer membrane. BCL-2 protein family is a key regulator of cell death. Thereby, the cell fate is decided by a complex network of interactions between pro- and anti-apoptotic members of the family, which govern mitochondrial outer membrane permeabilisation. Our multiscaling molecular dynamics simulations, consisting of spontaneous association of membrane-embedded transmembrane receptors at coarse-grained resolution, resolution transformation to atomistic resolution, and the refinement of the most often occurring interaction interfaces in atomistic simulations, complement the experimental investigations of Tobias Beigl and Prof. Frank Essman at the institute for clinical Pharmacology. Our joint efforts aim at shedding light on the molecular mechanisms of function of a prominent BCL-2 receptor, BOK, and its possible regulation by anti-apoptotic proteins.
Note. In order to be able to perform these simulations, Kristyna Pluhackova and Tobias Beigl have succeeded in acquiring a grant for computing time on the supercomputer HoreKa at KIT.
Researcher: Thomas Fellmeth
The ability of a cell to react to extracellular stimuli is enabled by a complex protein machinery based on G protein-coupled receptors (GPCRs) attached to the cell membrane and their intracellular interaction partners, G-proteins and arrestins. Due to their important roles in healthy and disease states, GPCRs are targeted by one third of all current drugs.
Complementing the atomic-force-microscopy investigations of Florian Wilhelm in the group of Prof. Daniel J. Müller at the ETH Zürich, we study the binding of PIP2, a lipidic messenger, to the β2-adrenergic receptor/β-arrestin2 complex and its impact on the complex structure and dynamics. Also, we mechanically separate β-arrestin2 from the receptor to unravel the relative stability of the complexes, the dissociation pathways, and the importance of individual residues. This knowledge is of particular pharmacological importance, as currently only the activation state of the receptor is targeted by pharmaceuticals. However, arrestin binding to the receptor competes with binding of its cognate G protein and causes receptor desensitization, thus opening new pathways for pharmacological intervention.
Researcher: Wenzel Gaßner