A deep unsupervised Model for Protein Design
The design of new functional proteins can tackle many of the problems humankind is facing today but so far has proven very challenging1. Analogies between protein sequences and human languages have been long noted and a summary of their most prominent similarities is described. Given the tremendous success of Natural Language Processing (NLP) methods in recent years, its application to protein research opens a fresh perspective, shifting from the current energy-function centered paradigm to an unsupervised learning approach based entirely on sequences. To explore this opportunity further we have pre-trained a generative language model on the entire protein sequence space. We find that our language model, ProtGPT2, effectively speaks the
Strong-field Response of complex Systems
The interaction of light with matter covers a large number of physical phenomena that we literally see in our everyday life. Early scientists mostly focused on investigations of electromagnetic radiation in the visible range and at low intensities, where material polarization responds linearly to incident electromagnetic fields. Utilizing the compute clusters at PC2, this project aims at simulating and interpreting the strong-field dynamics of real molecules and larger systems in a rigorous real-space real-time approach including non-linear strong-field effects such as photoionization and high-order harmonic generation of systems ranging from small (chiral) molecules over nano-systems to the condensed phase.
Molecular Dynamics Study of the Sodium/Potassium Channels HCN
Ion channels play a fundamental key role in all living organisms and are crucial for the signal transduction of neurons in higher animals. The hyperpolarization-activated cyclic nucleotide-gated (HCN) family of sodium/potassium channels are members of this protein family that are characterized by slow and weakly potassium selective inward current at hyperpolarizing voltages. HCN channels are expressed in a broad set of tissues in mammalia and are involved in an equally broad range of biological processes: in sinoatrial node cells of the heart, they are molecular facilitators of the pacemaker current (also known as ”funny current” If or Ih) which is required for subsequent generation of action potentials and ultimately leads to the
Flow around a Wind Turbine Blade at Reynolds Number 1 Million
The cost of energy produced by wind turbines has been undergoing a steady reduction. Wind energy supplied 15% of the electricity demand of the European Union in 2019. Since rotor blades are the determining component for both performance and loads, they are the objective of further optimizations. To obtain high efficiencies, an increased use of special aerodynamic profiles is observed possessing large areas of low-resistance, which means laminar flow is maintained. In order to design such profiles, it is necessary to include the laminar-turbulent transition in CFD simulations of wind turbine blades. Thus, the objective of the project is to carry out high-fidelity numerical simulations of the flow around a wind turbine blade at a realistic