Jan H. Meinke

Simulation of Top7-CFr: a transient helix extension guides folding.

Protein structures often feature β-sheets in which adjacent β-strands have large sequence separation. How the folding process orchestrates the formation and correct arrangement of these strands is not comprehensively understood. Particularly challenging are proteins in which β-strands at the N and C termini are neighbors in a β-sheet. The N-terminal β-strand is synthesized early on, but it can not bind to the C terminus before the chain is fully synthesized. During this time, there is a danger that the β-strand at the N terminus interacts with nearby molecules, leading to potentially harmful aggregates of incompletely folded proteins. Simulations of the C-terminal fragment of Top7 show that this risk of misfolding and aggregation can be avoided by a “caching” mechanism that relies on the “chameleon” behavior of certain segments.

The mont-blanc prototype: an alternative approach for HPC systems

High-performance computing (HPC) is recognized as one of the pillars for further progress in science, industry, medicine, and education. Current HPC systems are being developed to overcome emerging architectural challenges in order to reach Exascale level of performance, projected for the year 2020. The much larger embedded and mobile market allows for rapid development of intellectual property (IP) blocks and provides more flexibility in designing an application-specific system-on-chip (SoC), in turn providing the possibility in balancing performance, energy-efficiency, and cost. In the Mont-Blanc project, we advocate for HPC systems being built from such commodity IP blocks, currently used in embedded and mobile SoCs. As a first demonstrator of such an approach, we present the Mont-Blanc prototype; the first HPC system built with commodity SoCs, memories, and network interface cards (NICs) from the embedded and mobile domain, and off-the-shelf HPC networking, storage, cooling, and integration solutions. We present the systems architecture and evaluate both performance and energy efficiency. Further, we compare the systems abilities against a production level supercomputer. At the end, we discuss parallel scalability and estimate the maximum scalability point of this approach across a set of applications.

Aggregation of β-amyloid fragments

The authors study the folding and aggregation of six chains of the β-amyloid fragment 16–22 using Monte Carlo simulations. While the isolated fragment prefers a helical form at room temperature, in the system of six interacting fragments one observes both parallel and antiparallel β sheets below a crossover temperature Tx≈420K. The antiparallel sheets have lower energy and are therefore more stable. Above the nucleation temperature the aggregate quickly dissolves into widely separated, weakly interacting chains.

SMMP v. 3.0 - Simulating proteins and protein interactions in Python and Fortran

We describe a revised and updated version of the program package SMMP. SMMP is an open-source FORTRAN package for molecular simulation of proteins within the standard geometry model. It is designed as a simple and inexpensive tool for researchers and students to become familiar with protein simulation techniques. SMMP 3.0 sports a revised API increasing its flexibility, an implementation of the Lund force field, multi-molecule simulations, a parallel implementation of the energy function, Python bindings, and more.

Free-energy-driven folding and thermodynamics of the 67-residue protein GS-α3W—A large-scale Monte Carlo study

Utilizing the computational power of a few thousand processors on a BlueGene/P, we have explored the folding mechanism of the 67‐residue protein GS‐α3W. Results from our large‐scale simulation indicate a diffusion‐collision mechanism for folding. However, the lower‐than‐expected frequency of native‐like configurations at physiological temperatures indicates shortcomings of our energy function. Our results suggest that computational studies of large proteins call for redevelopment and reparametrization of force fields that in turn require extensive simulations only possible with the newly available supercomputers with computing powers reaching the petaflop range.

Protein simulations combining an all-atom force field with a Go term

Using a variant of parallel tempering, we study the changes in sampling within a simulation, when the all-atom model is coupled to a Go-like potential. We find that the native structure is not the lowest-energy configuration in the all-atom force field. Adding a Go term deforms the energy landscape in such a way that the native configuration becomes the global minimum but does not lead to faster thermalization.

Folding of Top7 in unbiased all-atom Monte Carlo simulations

For computational studies of protein folding, proteins with both helical and β‐sheet secondary structure elements are very challenging, as they expose subtle biases of the physical models. Here, we present reproducible folding of a 92 residue α/β protein (residues 3–94 of Top7, PDB ID: 1QYS) in computer simulations starting from random initial conformations using a transferable physical model which has been previously shown to describe the folding and thermodynamic properties of about 20 other smaller proteins of different folds. Top7 is a de novo designed protein with two α‐helices and a five stranded β‐sheet. Experimentally, it is known to be unusually stable for its size, and its folding transition distinctly deviates from the two‐state behavior commonly seen in natural single domain proteins. In our all‐atom implicit solvent parallel tempering Monte Carlo simulations, Top7 shows a rapid transition to a group of states with high native‐like secondary structure, and a much slower subsequent transition to the native state with a root mean square deviation of about 3.5 Å from the experimentally determined structure. Consistent with experiments, we find Top7 to be thermally extremely stable, although the simulations also find a large number of very stable non‐native states with high native‐like secondary structure. Proteins 2013; 81:1446–1456.

Ground state nonuniversality in the random-field Ising model.

Two attractive and often used ideas, namely, universality and the concept of a zero-temperature fixed point, are violated in the infinite-range random-field Ising model. In the ground state we show that the exponents can depend continuously on the disorder and so are nonuniversal. However, we also show that at finite temperature the thermal order-parameter exponent 1/2 is restored so that temperature is a relevant variable. Broader implications of these results are discussed.

GPUMAFIA: efficient subspace clustering with MAFIA on GPUs

Clustering, i.e., the identification of regions of similar objects in a multi-dimensional data set, is a standard method of data analytics with a large variety of applications. For high-dimensional data, subspace clustering can be used to find clusters among a certain subset of data point dimensions and alleviate the curse of dimensionality. In this paper we focus on the MAFIA subspace clustering algorithm and on using GPUs to accelerate the algorithm. We first present a number of algorithmic changes and estimate their effect on computational complexity of the algorithm. These changes improve the computational complexity of the algorithm and accelerate the sequential version by 1---2 orders of magnitude on practical datasets while providing exactly the same output. We then present the GPU version of the algorithm, which for typical datasets provides a further 1---2 orders of magnitude speedup over a single CPU core or about an order of magnitude over a typical multi-core CPU. We believe that our faster implementation widens the applicability of MAFIA and subspace clustering.

Critical Manifolds in Polycrystalline Grain Structures

With the development of new, fully three-dimensional metallographic techniques, there is considerable interest in characterizing three-dimensional microstructures in ways that go beyond twodimensional stereology. One characteristic of grain structures is the surface of lowest energy across the microstructure, termed the critical manifold (CM). When the grain boundaries are sufficiently weak, the CM lies entirely on grain boundaries, while when the grain boundaries are strong, cleavage occurs. A scaling theory for the cleavage to intergranular transition of CMs is developed. We find that a critical length scale exists, so that on short length scales cleavage is observed, while at long length scales the CM is rough. CMs for realistic polycrystalline grain structures, determined by a network optimization algorithm, are used to verify the analysis.