Timo Strunk

Selective Dispersion of Single-Walled Carbon Nanotubes with Specific Chiral Indices by Poly(N-decyl-2,7-carbazole)

Physico-chemical methods to sort single-walled carbon nanotubes (SWNTs) by chiral index are presently lacking but are required for in-depth experimental analysis and also for potential future applications of specific species. Here we report the unexpected selectivity of poly(N-decyl-2,7-carbazole) to almost exclusively disperse semiconducting SWNTs with differences of their chiral indices (n - m) ≥ 2 in toluene. The observed selectivity complements perfectly the dispersing features of the fluorene analogue poly(9,9-dialkyl-2,7-fluorene), which disperses semiconducting SWNTs with (n - m) ≤ 2 in toluene. The dispersed samples are further purified by density gradient centrifugation and analyzed by photoluminescence excitation spectroscopy. All-atom molecular modeling with decamer model compounds of the polymers and (10,2) and (7,6) SWNTs suggests differences in the π-π stacking interaction as origin of the selectivity. We observe energetically favored complexes between the (10,2) SWNT and the carbazole decamer and between the (7,6) SWNT and the fluorene decamer, respectively. These findings demonstrate that subtle structural changes of polymers lead to selective solvation of different families of carbon nanotubes. Furthermore, chemical screening of closely related polymers may pave the way toward simple, low-cost, and index-specific isolation of SWNTs.

Structural model of the gas vesicle protein GvpA and analysis of GvpA mutants in vivo

Gas vesicles are gas‐filled protein structures increasing the buoyancy of cells. The gas vesicle envelope is mainly constituted by the 8 kDa protein GvpA forming a wall with a water excluding inner surface. A structure of GvpA is not available; recent solid‐state NMR results suggest a coil‐α‐β‐β‐α‐coil fold. We obtained a first structural model of GvpA by high‐performance de novo modelling. Attenuated total reflection (ATR)‐Fourier transform infrared spectroscopy (FTIR) supported this structure. A dimer of GvpA was derived that could explain the formation of the protein monolayer in the gas vesicle wall. The hydrophobic inner surface is mainly constituted by anti‐parallel β‐strands. The proposed structure allows the pinpointing of contact sites that were mutated and tested for the ability to form gas vesicles in haloarchaea. Mutations in α‐helix I and α‐helix II, but also in the β‐turn affected the gas vesicle formation, whereas other alterations had no effect. All mutants supported the structural features deduced from the model. The proposed GvpA dimers allow the formation of a monolayer protein wall, also consistent with protease treatments of isolated gas vesicles.

Six Hydrophobins Are Involved in Hydrophobin Rodlet Formation in Aspergillus nidulans and Contribute to Hydrophobicity of the Spore Surface

Hydrophobins are amphiphilic proteins able to self-assemble at water-air interphases and are only found in filamentous fungi. In Aspergillus nidulans two hydrophobins, RodA and DewA, have been characterized, which both localize on the conidiospore surface and contribute to its hydrophobicity. RodA is the constituent protein of very regularly arranged rodlets, 10 nm in diameter. Here we analyzed four more hydrophobins, DewB-E, in A. nidulans and found that all six hydrophobins contribute to the hydrophobic surface of the conidiospores but only deletion of rodA caused loss of the rodlet structure. Analysis of the rodlets in the dewB-E deletion strains with atomic force microscopy revealed that the rodlets appeared less robust. Expression of DewA and DewB driven from the rodA promoter and secreted with the RodA secretion signal in a strain lacking RodA, restored partly the hydrophobicity. DewA and B were able to form rodlets to some extent but never reached the rodlet structure of RodA. The rodlet-lacking rodA-deletion strain opens the possibility to systematically study rodlet formation of other natural or synthetic hydrophobins.

Derivatives of molecular surface area and volume: Simple and exact analytical formulas

The computational effort of biomolecular simulations can be significantly reduced by means of implicit solvent models in which the energy generally contains a correction depending on the surface area and/or the volume of the molecule. In this article, we present simple derivation of exact, easy‐to‐use analytical formulas for these quantities and their derivatives with respect to atomic coordinates. In addition, we provide an efficient, linear‐scaling algorithm for the construction of the power diagram required for practical implementation of these formulas. Our approach is implemented in a C++ header‐only template library.

Engineering hydrophobin DewA to generate surfaces that enhance adhesion of human but not bacterial cells

Hydrophobins are fungal proteins with the ability to form immunologically inert membranes of high stability, properties that makes them attractive candidates for orthopaedic implant coatings. Cell adhesion on the surface of such implants is necessary for better integration with the neighbouring tissue; however, hydrophobin surfaces do not mediate cell adhesion. The aim of this project was therefore to investigate whether the class I hydrophobin DewA from Aspergillus nidulans can be functionalized for use on orthopaedic implant surfaces. DewA variants bearing either one RGD sequence or the laminin globular domain LG3 binding motif were engineered. The surfaces of both variants showed significantly increased adhesion of mesenchymal stem cells (MSCs), osteoblasts, fibroblasts and chondrocytes; in contrast, the insertion of binding motifs RGD and LG3 in DewA did not increase Staphylococcus aureus adhesion to the hydrophobin surfaces. Proliferation of MSCs and their osteogenic, chondrogenic and adipogenic differentiation potential were not affected on these surfaces. The engineered surfaces therefore enhanced MSC adhesion without interfering with their functionality or leading to increased risk of bacterial infection.

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.

Probing hot spots on protein-protein interfaces with all-atom free-energy simulation

Modulation of protein-protein interactions by competitive small-molecule binding emerges as a promising avenue for drug discovery. Hot spots, i.e., amino acids with important contributions to the overall interaction energy, provide useful targets within these interfaces. To avoid time-consuming mutagenesis experiments, computational alanine screening has been developed for the prediction of hot spots based on existing structural information. Here we use the all-atom free-energy force field PFF02 to identify important amino acid residues in the complexes of the chemokine interleukin-8 (CXCL8) and an N-terminal peptide of its cognate receptor CXCR1, and of ERBIN, a molecular marker of the basolateral membrane in epithelial cells, in complex with the ERBIN-binding domain of tyrosin kinase ERBB2. The results of our analysis agree with available experimental functional assays, indicating that this approach is suitable for computational alanine screening and may help to identify competitive peptides as starting points for the development of inhibitors of protein-protein interactions for pharmaceutically relevant targets.

Rational In Silico Design of an Organic Semiconductor with Improved Electron Mobility

Organic semiconductors find a wide range of applications, such as in organic light emitting diodes, organic solar cells, and organic field effect transistors. One of their most striking disadvantages in comparison to crystalline inorganic semiconductors is their low charge-carrier mobility, which manifests itself in major device constraints such as limited photoactive layer thicknesses. Trial-and-error attempts to increase charge-carrier mobility are impeded by the complex interplay of the molecular and electronic structure of the material with its morphology. Here, the viability of a multiscale simulation approach to rationally design materials with improved electron mobility is demonstrated. Starting from one of the most widely used electron conducting materials (Alq3 ), novel organic semiconductors with tailored electronic properties are designed for which an improvement of the electron mobility by three orders of magnitude is predicted and experimentally confirmed.

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.

Charge carrier mobility and electronic properties of Al(Op)3: impact of excimer formation

Summary We have studied the electronic properties and the charge carrier mobility of the organic semiconductor tris(1-oxo-1H-phenalen-9-olate)aluminium(III) (Al(Op)3) both experimentally and theoretically. We experimentally estimated the HOMO and LUMO energy levels to be −5.93 and −3.26 eV, respectively, which were close to the corresponding calculated values. Al(Op)3 was successfully evaporated onto quartz substrates and was clearly identified in the absorption spectra of both the solution and the thin film. A structured steady state fluorescence emission was detected in solution, whereas a broad, red-shifted emission was observed in the thin film. This indicates the formation of excimers in the solid state, which is crucial for the transport properties. The incorporation of Al(Op)3 into organic thin film transistors (TFTs) was performed in order to measure the charge carrier mobility. The experimental setup detected no electron mobility, while a hole mobility between 0.6 × 10−6 and 2.1 × 10−6 cm2·V−1·s−1 was measured. Theoretical simulations, on the other hand, predicted an electron mobility of 9.5 × 10−6 cm2·V−1·s−1 and a hole mobility of 1.4 × 10−4 cm2·V−1·s−1. The theoretical simulation for the hole mobility predicted an approximately one order of magnitude higher hole mobility than was observed in the experiment, which is considered to be in good agreement. The result for the electron mobility was, on the other hand, unexpected, as both the calculated electron mobility and chemical common sense (based on the capability of extended aromatic structures to efficiently accept and delocalize additional electrons) suggest more robust electron charge transport properties. This discrepancy is explained by the excimer formation, whose inclusion in the multiscale simulation workflow is expected to bring the theoretical simulation and experiment into agreement.