Moritz Wolf

Structure of the Membrane Anchor of Pestivirus Glycoprotein Erns, a Long Tilted Amphipathic Helix

Erns is an essential virion glycoprotein with RNase activity that suppresses host cellular innate immune responses upon being partially secreted from the infected cells. Its unusual C-terminus plays multiple roles, as the amphiphilic helix acts as a membrane anchor, as a signal peptidase cleavage site, and as a retention/secretion signal. We analyzed the structure and membrane binding properties of this sequence to gain a better understanding of the underlying mechanisms. CD spectroscopy in different setups, as well as Monte Carlo and molecular dynamics simulations confirmed the helical folding and showed that the helix is accommodated in the amphiphilic region of the lipid bilayer with a slight tilt rather than lying parallel to the surface. This model was confirmed by NMR analyses that also identified a central stretch of 15 residues within the helix that is fully shielded from the aqueous layer, which is C-terminally followed by a putative hairpin structure. These findings explain the strong membrane binding of the protein and provide clues to establishing the Erns membrane contact, processing and secretion.

SIMONA 1.0: An efficient and versatile framework for stochastic simulations of molecular and nanoscale systems

Molecular simulation methods have increasingly contributed to our understanding of molecular and nanoscale systems. However, the family of Monte Carlo techniques has taken a backseat to molecular dynamics based methods, which is also reflected in the number of available simulation packages. Here, we report the development of a generic, versatile simulation package for stochastic simulations and demonstrate its application to protein conformational change, protein–protein association, small‐molecule protein docking, and simulation of the growth of nanoscale clusters of organic molecules. Simulation of molecular and nanoscale systems (SIMONA) is easy to use for standard simulations via a graphical user interface and highly parallel both via MPI and the use of graphical processors. It is also extendable to many additional simulations types. Being freely available to academic users, we hope it will enable a large community of researchers in the life‐ and materials‐sciences to use and extend SIMONA in the future. SIMONA is available for download under http://int.kit.edu/nanosim/simona.

Peptide structure prediction using distributed volunteer computing networks

Recent investigations to develop novel antimicrobial, antibiotical drugs have focused on the development of artificial protein peptides. As short peptides are naturally involved in many important biological processes in the cell and therefore target many kinds of cells. To functionalize peptides it is vital to design peptides, which can differentially target bacterial and eucariotic cells. Although the length of the peptides investigated in this study was limited to 16 amino acids, the number of possible peptide sequences is still too large to synthesize them in a trial- and error manner, therefore requiring a method for directed, but also high-througput peptide design. By predicting the structure of peptide proteins, this design process can be supported through structure-function analysis and peptide-membrane interaction simulation. In this investigation we could predict peptide structures de-novo, i.e. with the sequence information alone, using a massively parallel simulation scheme. We sample a sizable fraction of the peptide’s conformational space using Monte-Carlo simulations in the free-energy forcefield PFF02 on the volunteer computing network POEM@HOME. This forcefield models the protein’s native conformation as the global minimum of the free-energy. We could identify peptides of different topologies in a completely automated manner, which allows for the high-throughput screening of large peptide databases for their structural features, which would allow the rapid protopying of peptides needed for novel peptide design.