pyMBE: The Python-based molecule builder for ESPResSo.

We present the Python-based Molecule Builder for ESPResSo (pyMBE), an open source software application to design custom coarse-grained (CG) models, as well as pre-defined models of polyelectrolytes, peptides, and globular proteins in the Extensible Simulation Package for Research on Soft Matter (ESPResSo). The Python interface of ESPResSo offers a flexible framework, capable of building custom CG models from scratch. As a downside, building CG models from scratch is prone to mistakes, especially for newcomers in the field of CG modeling, or for molecules with complex architectures. The pyMBE module builds CG models in ESPResSo using a hierarchical bottom-up approach, providing a robust tool to automate the setup of CG models and helping new users prevent common mistakes. ESPResSo features the constant pH (cpH) and grand-reaction (G-RxMC) methods, which have been designed to study chemical reaction equilibria in macromolecular systems with many reactive species. However, setting up these methods for systems, which contain several types of reactive groups, is an error-prone task, especially for beginners. The pyMBE module enables the automatic setup of cpH and G-RxMC simulations in ESPResSo, lowering the barrier for newcomers and opening the door to investigate complex systems not studied with these methods yet. To demonstrate some of the applications of pyMBE, we showcase several case studies where we successfully reproduce previously published simulations of charge-regulating peptides and globular proteins in bulk solution and weak polyelectrolytes in dialysis. The pyMBE module is publicly available as a GitHub repository (https://github.com/pyMBE-dev/pyMBE), which includes its source code and various sample and test scripts, including the ones that we used to generate the data presented in this article.

Hedgehog is relayed through dynamic heparan sulfate interactions to shape its gradient.

Cellular differentiation is directly determined by concentration gradients of morphogens. As a central model for gradient formation during development, Hedgehog (Hh) morphogens spread away from their source to direct growth and pattern formation in Drosophila wing and eye discs. What is not known is how extracellular Hh spread is achieved and how it translates into precise gradients. Here we show that two separate binding areas located on opposite sides of the Hh molecule can interact directly and simultaneously with two heparan sulfate (HS) chains to temporarily cross-link the chains. Mutated Hh lacking one fully functional binding site still binds HS but shows reduced HS cross-linking. This, in turn, impairs Hhs ability to switch between both chains in vitro and results in striking Hh gradient hypomorphs in vivo. The speed and propensity of direct Hh switching between HS therefore shapes the Hh gradient, revealing a scalable design principle in morphogen-patterned tissues.

Computational model predicts protein binding sites of a luminescent ligand equipped with guanidiniocarbonyl-pyrrole groups.

The 14-3-3 protein family, one of the first discovered phosphoserine/phosphothreonine binding proteins, has attracted interest not only because of its important role in the cell regulatory processes but also due to its enormous number of interactions with other proteins. Here, we use a computational approach to predict the binding sites of the designed hybrid compound featuring aggregation-induced emission luminophores as a potential supramolecular ligand for 14-3-3ζ in the presence and absence of C-Raf peptides. Our results suggest that the area above and below the central pore of the dimeric 14-3-3ζ protein is the most probable binding site for the ligand. Moreover, we predict that the position of the ligand is sensitive to the presence of phosphorylated C-Raf peptides. With a series of experiments, we confirmed the computational prediction of two C 2 related, dominating binding sites on 14-3-3ζ that may bind to two of the supramolecular ligand molecules.

Specific inhibition of the Survivin-CRM1 interaction by peptide-modified molecular tweezers.

Survivin's dual function as apoptosis inhibitor and regulator of cell proliferation is mediated via its interaction with the export receptor CRM1. This protein-protein interaction represents an attractive target in cancer research and therapy. Here, we report a sophisticated strategy addressing Survivin's nuclear export signal (NES), the binding site of CRM1, with advanced supramolecular tweezers for lysine and arginine. These were covalently connected to small peptides resembling the natural, self-complementary dimer interface which largely overlaps with the NES. Several biochemical methods demonstrated sequence-selective NES recognition and interference with the critical receptor interaction. These data were strongly supported by molecular dynamics simulations and multiscale computational studies. Rational design of lysine tweezers equipped with a peptidic recognition element thus allowed to address a previously unapproachable protein surface area. As an experimental proof-of-principle for specific transport signal interference, this concept should be transferable to any protein epitope with a flanking well-accessible lysine.

Modeling the current modulation of bundled DNA structures in nanopores.

We investigate the salt-dependent current modulation of bundled DNA nanostructures in a nanopore. To this end, we developed four simulation models for a 2 × 2 origami structure with increasing level of detail ranging from the mean-field level to an all-atom representation of the DNA structure. We observe a consistent pore conductivity as a function of salt concentration for all four models. However, a comparison of our data to recent experimental investigations on similar systems displays significant deviations. We discuss possible reasons for the discrepancies and propose extensions to our models for future investigations.

Accelerated trypsin autolysis by affinity polymer templates.

Self-cleavage of proteins is an important natural process that is difficult to control externally. Recently a new mechanism for the accelerated autolysis of trypsin was discovered involving polyanionic template polymers; however it relies on unspecific interactions and is inactive at elevated salt loads. We have now developed affinity copolymers that bind to the surface of proteases by specific recognition of selected amino acid residues. These are highly efficient trypsin inhibitors with low nanomolar IC50 levels and operate at physiological conditions. In this manuscript we show how these affinity copolymers employ the new mechanism of polymer-assisted self-digest (PAS) and act as a template for multiple protease molecules. Their elevated local concentration leads to accelerated autolysis on the accessible surface area and shields complexed areas. The resulting extremely efficient trypsin inhibition was studied by SDS-PAGE, gel filtration, CD, CZE and ESI-MS. We also present a simple theoretical model that simulates most experimental findings and confirms them as a result of multivalency and efficient reversible templating. For the first time, mass spectrometric kinetic analysis of the released peptide fragments gives deeper insight into the underlying mechanism and reveals that polymer-bound trypsin cleaves much more rapidly with low specificity at predominantly uncomplexed surface areas.

An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action.

Research software has become a central asset in academic research. It optimizes existing and enables new research methods, implements and embeds research knowledge, and constitutes an essential research product in itself. Research software must be sustainable in order to understand, replicate, reproduce, and build upon existing research or conduct new research effectively. In other words, software must be available, discoverable, usable, and adaptable to new needs, both now and in the future. Research software therefore requires an environment that supports sustainability. Hence, a change is needed in the way research software development and maintenance are currently motivated, incentivized, funded, structurally and infrastructurally supported, and legally treated. Failing to do so will threaten the quality and validity of research. In this paper, we identify challenges for research software sustainability in Germany and beyond, in terms of motivation, selection, research software engineering personnel, funding, infrastructure, and legal aspects. Besides researchers, we specifically address political and academic decision-makers to increase awareness of the importance and needs of sustainable research software practices. In particular, we recommend strategies and measures to create an environment for sustainable research software, with the ultimate goal to ensure that software-driven research is valid, reproducible and sustainable, and that software is recognized as a first class citizen in research. This paper is the outcome of two workshops run in Germany in 2019, at deRSE19 - the first International Conference of Research Software Engineers in Germany - and a dedicated DFG-supported follow-up workshop in Berlin.

Rational Design, Binding Studies, and Crystal-Structure Evaluation of the First Ligand Targeting the Dimerization Interface of the 14-3-3ζ Adapter Protein.

14-3-3 Proteins play a central role in signalling pathways in cells: they interact as gatekeeper proteins with a huge number of binding partners. Their function as hub for intracellular communication can explain why these adapter proteins are associated with a wide range of diseases. How they control the various cellular mechanisms is still unclear, but it is assumed that the dimeric nature of the 14-3-3 proteins plays a key role in their activity. Here, we present, to the best of our knowledge, the first example of a small molecule binding to the 14-3-3ζ dimerisation interface. This compound was designed by rational in silico optimisation of a peptidic ligand identified from biochemical screening of a peptidic library, and the binding was characterised by UV/Vis spectroscopy, microscale thermophoresis, multiscale simulations, and X-ray crystallography.

Locating Large, Flexible Ligands on Proteins.

Many biologically important ligands of proteins are large, flexible, and in many cases charged molecules that bind to extended regions on the protein surface. It is infeasible or expensive to locate such ligands on proteins with standard methods such as docking or molecular dynamics (MD) simulation. The alternative approach proposed here is scanning of a spatial and angular grid around the protein with smaller fragments of the large ligand. Energy values for complete grids can be computed efficiently with a well-known fast Fourier transform-accelerated algorithm and a physically meaningful interaction model. We show that the approach can readily incorporate flexibility of the protein and ligand. The energy grids (EGs) resulting from the ligand fragment scans can be transformed into probability distributions and then directly compared to probability distributions estimated from MD simulations and experimental structural data. We test the approach on a diverse set of complexes between proteins and large, flexible ligands, including a complex of sonic hedgehog protein and heparin, three heparin sulfate substrates or nonsubstrates of an epimerase, a multibranched supramolecular ligand that stabilizes a protein-peptide complex, a flexible zwitterionic ligand that binds to a surface basin of a Kringle domain, and binding of ATP to a flexible site of an ion channel. In all cases, the EG approach gives results that are in good agreement with experimental data or MD simulations.