German Research School for Simulation Sciences

Conformational changes are crucial for the catalytic action of many enzymes. A prototypical and well-studied example is loop opening and closure in triosephosphate isomerase (TIM), which is thought to determine the rate of catalytic turnover in many circumstances. Specifically, TIM loop 6 "grips" the phosphodianion of the substrate and, together with a change in loop 7, sets up the TIM active site for efficient catalysis. Crystal structures of TIM typically show an open or a closed conformation of loop 6, with the tip of the loop moving ∼7 Å between conformations. Many studies have interpreted this motion as a two-state, rigid-body transition. Here, we use extensive molecular dynamics simulations, with both conventional and enhanced sampling techniques, to analyze loop motion in apo and substrate-bound TIM in detail, using five crystal structures of the dimeric TIM from Saccharomyces cerevisiae. We find that loop 6 is highly flexible and samples multiple conformational states. Empirical valence bond simulations of the first reaction step show that slight displacements away from the fully closed-loop conformation can be sufficient to abolish most of the catalytic activity; full closure is required for efficient reaction. The conformational change of the loops in TIM is thus not a simple "open and shut" case and is crucial for its catalytic action. Our detailed analysis of loop motion in a highly efficient enzyme highlights the complexity of loop conformational changes and their role in biological catalysis.

Ginzburg-Landau theory describes phase transitions as the competition between energy and entropy: The ordered phase has lower energy, while the disordered phase has larger entropy. When heating the system, ordering is reduced entropically until it vanishes at the critical temperature. This established picture implicitly assumes that the energy difference between ordered and disordered phase does not change with temperature. We show that for the Mott insulator KCuF3 this assumption is strongly violated: thermal expansion energetically stabilizes the orbitally-ordered phase to such and extent that no phase transition is observed. This new mechanism explains not only the absence of a phase transition in KCuF3 but even suggests the possibility of an inverted transition in closed-shell systems, where the ordered phase emerges only at high temperatures.

The ability of a drug to cross the intestine-blood barrier is a key quantity for drug design and employment and is normally quantified by the permeability coefficient P, often evaluated in the so-called Caco-2 assay. This assay is based on measuring the initial growth rate of the concentration of the drug beyond the cellular barrier but not its steady-state flux through the membrane. This might lead to confusion since, in the case of lipophilic drugs, the initial slope is strongly affected by the retention of the drug in the membrane. This effect is well known but seldom considered in the assay. Here, we exploit all-atoms molecular dynamics and bias exchange metadynamics to calculate the concentration of two lipophilic drugs across a model membrane as a function of time. This allows estimating both the steady-state flux and the initial slope of the concentration growth and comparing Caco-2 and steady-state estimates of P. We show that our computational procedure is able to reproduce the experimental values, although these may differ from the permeability coefficients by orders of magnitude. Our findings are generalized by a simplified one-dimensional model of the permeation process that may act as a roadmap to assess which measure of membrane permeability would be more appropriate and, consequently, whether retention corrections should be included in estimates based on Caco-2 assays.

Motivated by recent experiments, we present here a detailed theoretical analysis of the use of carbon-based conductive tips in scanning tunnelling microscopy. In particular, we employ ab initio methods based on density functional theory to explore a graphitic, an amorphous carbon and two diamond-like tips for imaging with a scanning tunnelling microscope (STM), and we compare them with standard metallic tips made of gold and tungsten. We investigate the performance of these tips in terms of the corrugation of the STM images acquired when scanning a single graphene sheet. Moreover, we analyse the impact of the tip-sample distance and show that it plays a fundamental role in the resolution and symmetry of the STM images. We also explore in depth how the adsorption of single atoms and molecules in the tip apexes modifies the STM images and demonstrate that, in general, it leads to an improved image resolution. The ensemble of our results provides strong evidence that carbon-based tips can significantly improve the resolution of STM images, as compared to more standard metallic tips, which may open a new line of research in scanning tunnelling microscopy.

Density functional/molecular dynamics simulations have been performed to determine structural and other properties of amorphous Ag/Ge/S and Ge/S alloys. In the former, the calculations have been combined with experimental data (x-ray and neutron diffraction, extended x-ray absorption fine structure). Ag/Ge/As alloys have high ionic conductivity and are among the most promising candidates for future memristor technology. We find excellent agreement between the experimental results and large-scale (500 atoms) simulations in Ag/Ge/S, and we compare and contrast the structures of Ge/S and Ag/Ge/S. The calculated electronic structures, vibrational densities of states, ionic mobilities, and cavity distributions of the amorphous materials are discussed and compared with data on crystalline phases where available. The high mobility of Ag in solid state electrolyte applications is related to the presence of cavities and can occur via jumps to a neighbouring vacant site.

Cation selective channels constitute the gate for ion currents through the cell membrane. Here we present an improved statistical mechanical model based on atomistic structural information, cation hydration state and without tuned parameters that reproduces the selectivity of biological Na+ and Ca2+ ion channels. The importance of the inclusion of step-wise cation hydration in these results confirms the essential role partial dehydration plays in the bacterial Na+ channels. The model, proven reliable against experimental data, could be straightforwardly used for designing Na+ and Ca2+ selective nanopores.

Sirtuin 2 (SIRT2) is a NAD+-dependent deacetylase that has been associated with neurodegeneration and cancer. SIRT2 is composed of a central catalytic domain, the structure of which has been solved, and N- and C-terminal extensions that are thought to control SIRT2 function. However structural information of these N- and C-terminal regions is missing. Here, we provide the first full-length molecular models of SIRT2 in the absence and presence of NAD+. We also predict the structural alterations associated with phosphorylation of SIRT2 at S331, a modification that inhibits catalytic activity. Bioinformatics tools and molecular dynamics simulations, complemented by in vitro deacetylation assays, provide a consistent picture based on which the C-terminal region of SIRT2 is suggested to function as an autoinhibitory region. This has the capacity to partially occlude the NAD+ binding pocket or stabilize the NAD+ in a non-productive state. Furthermore, our simulations suggest that the phosphorylation at S331 causes large conformational changes in the C-terminal region that enhance the autoinhibitory activity, consistent with our previous findings that phosphorylation of S331 by cyclin-dependent kinases inhibits SIRT2 catalytic activity. The molecular insight into the role of the C-terminal region in controlling SIRT2 function described in this study may be useful for future design of selective inhibitors targeting SIRT2 for therapeutic applications.

Discovery of parallelization opportunities in sequential programs can greatly reduce the time and effort required to parallelize any application. Identification and analysis of code that contains little to no internal parallelism can also help expose potential parallelism. This paper provides a technique to identify a block of code called Computational Unit (CU) that performs a unit of work in a program. A CU can assist in discovering the potential parallelism in a sequential program by acting as a basic building block for tasks. CUs are used along with dynamic analysis information to identify the tasks that contain tightly coupled code within them. This process in turn reveals the tasks that are weakly dependent or independent. The independent tasks can be run in parallel and the dependent tasks can be analyzed to check if the dependences can be resolved. To evaluate our technique, different benchmark applications are parallelized using our identified tasks and the speedups are reported. In addition, existing parallel implementations of the applications are compared with the identified tasks for the respective applications.

Intrinsically disordered proteins (IDPs) form biologically active complexes that can retain a high degree of conformational disorder, escaping structural characterization by conventional approaches. An example is offered by the complex between the intrinsically disordered N(TAIL) domain and the phosphoprotein X domain (P(XD)) from measles virus (MeV). Here, distinct conformers of the complex are detected by electrospray ionization-mass spectrometry (ESI-MS) and ion mobility (IM) techniques yielding estimates for the solvent-accessible surface area (SASA) in solution and the average collision cross-section (CCS) in the gas phase. Computational modeling of the complex in solution, based on experimental constraints, provides atomic-resolution structural models featuring different levels of compactness. The resulting models indicate high structural heterogeneity. The intermolecular interactions are predominantly hydrophobic, not only in the ordered core of the complex, but also in the dynamic, disordered regions. Electrostatic interactions become involved in the more compact states. This system represents an illustrative example of a hydrophobic complex that could be directly detected in the gas phase by native mass spectrometry. This work represents the first attempt to modeling the entire N(TAIL) domain bound to P(XD) at atomic resolution.

Efficient resource discovery plays a vital role in the effective management of resources and applications in heterogeneous computing environments. Therefore, the knowledge of applications' behavior and resources' usage pattern improves resource discovery decisions. This knowledge can be provided for the resource discovery mechanism by cooperating with the load balancing mechanism. In this paper, we formulate their cooperation by considering some parameters that represent applications' behavior and resources' usage patterns and extract the relation between them to introduce a formula using mathematical methods. Further, the resource discovery mechanism uses the formula to predict resources' load before assigning them new processes and thus it prevents resource overloading which happens frequently in computing environments.