Large Oligomeric Complex Structures Can Be Computationally Assembled by Efficiently Combining Docked Interfaces

Macromolecular oligomeric assemblies are involved in many biochemical processes of living organisms. The benefits of such assemblies in crowded cellular environments include increased reaction rates, efficient feedback regulation, cooperativity and protective functions. However, an atom‐level structural determination of large assemblies is challenging due to the size of the complex and the difference in binding affinities of the involved proteins. In this study, we propose a novel combinatorial greedy algorithm for assembling large oligomeric complexes from information on the approximate position of interaction interfaces of pairs of monomers in the complex. Prior information on complex symmetry is not required but rather the symmetry is inferred during assembly. We implement an efficient geometric score, the transformation match score, that bypasses the model ranking problems of state‐of‐the‐art scoring functions by scoring the similarity between the inferred dimers of the same monomer simultaneously with different binding partners in a (sub)complex with a set of pregenerated docking poses. We compiled a diverse benchmark set of 308 homo and heteromeric complexes containing 6 to 60 monomers. To explore the applicability of the method, we considered 48 sets of parameters and selected those three sets of parameters, for which the algorithm can correctly reconstruct the maximum number, namely 252 complexes (81.8%) in, at least one of the respective three runs. The crossvalidation coverage, that is, the mean fraction of correctly reconstructed benchmark complexes during crossvalidation, was 78.1%, which demonstrates the ability of the presented method to correctly reconstruct topology of a large variety of biological complexes. Proteins 2015; 83:1887–1899. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc

An Introductory Guide to Aligning Networks Using SANA, the Simulated Annealing Network Aligner.

Sequence alignment has had an enormous impact on our understanding of biology, evolution, and disease. The alignment of biological networks holds similar promise. Biological networks generally model interactions between biomolecules such as proteins, genes, metabolites, or mRNAs. There is strong evidence that the network topology-the "structure" of the network-is correlated with the functions performed, so that network topology can be used to help predict or understand function. However, unlike sequence comparison and alignment-which is an essentially solved problem-network comparison and alignment is an NP-complete problem for which heuristic algorithms must be used.Here we introduce SANA, the Simulated Annealing Network Aligner. SANA is one of many algorithms proposed for the arena of biological network alignment. In the context of global network alignment, SANA stands out for its speed, memory efficiency, ease-of-use, and flexibility in the arena of producing alignments between two or more networks. SANA produces better alignments in minutes on a laptop than most other algorithms can produce in hours or days of CPU time on large server-class machines. We walk the user through how to use SANA for several types of biomolecular networks

Discrete molecular dynamics simulations of peptide aggregation

We study the aggregation of peptides using the discrete molecular dynamics simulations. At temperatures above the alpha-helix melting temperature of a single peptide, the model peptides aggregate into a multi-layer parallel beta-sheet structure. This structure has an inter-strand distance of 0.48 nm and an inter-sheet distance of 1.0 nm, which agree with experimental observations. In this model, the hydrogen bond interactions give rise to the inter-strand spacing in beta-sheets, while the Go interactions among side chains make beta-strands parallel to each other and allow beta-sheets to pack into layers. The aggregates also contain free edges which may allow for further aggregation of model peptides to form elongated fibrils.Comment: 15 pages, 8 figure

Differential directed flow in Au+Au collisions

We present experimental data on directed flow in semi-central Au+Au collisions at incident energies from 90 to 400 A MeV. For the first time for this energy domain, the data are presented in a transverse momentum differential way. We study the first order Fourier coefficient v1 for different particle species and establish a gradual change of its patterns as a function of incident energy and for different regions in rapidity.Comment: 5 pages, Latex, 5 eps figures, accepted for publication in Phys. Rev. C (Rapid Communications). Data files available at http://www-linux.gsi.de/~andronic/fopi/v1.htm

Directed flow in Au+Au, Xe+CsI and Ni+Ni collisions and the nuclear equation of state

We present new experimental data on directed flow in collisions of Au+Au, Xe+CsI and Ni+Ni at incident energies from 90 to 400A MeV. We study the centrality and system dependence of integral and differential directed flow for particles selected according to charge. All the features of the experimental data are compared with Isospin Quantum Molecular Dynamics (IQMD) model calculations in an attempt to extract information about the nuclear matter equation of state (EoS). We show that the combination of rapidity and transverse momentum analysis of directed flow allow to disentangle various parametrizations in the model. At 400A MeV, a soft EoS with momentum dependent interactions is best suited to explain the experimental data in Au+Au and Xe+CsI, but in case of Ni+Ni the model underpredicts flow for any EoS. At 90A MeV incident beam energy, none of the IQMD parametrizations studied here is able to consistently explain the experimental data.Comment: RevTeX, 20 pages, 30 eps figures, accepted for publication in Phys. Rev. C. Data files available at http://www.gsi.de/~fopiwww/pub

The search for the ideal biocatalyst

While the use of enzymes as biocatalysts to assist in the industrial manufacture of fine chemicals and pharmaceuticals has enormous potential, application is frequently limited by evolution-led catalyst traits. The advent of designer biocatalysts, produced by informed selection and mutation through recombinant DNA technology, enables production of process-compatible enzymes. However, to fully realize the potential of designer enzymes in industrial applications, it will be necessary to tailor catalyst properties so that they are optimal not only for a given reaction but also in the context of the industrial process in which the enzyme is applied

The Genomics of Disulfide Bonding and Protein Stabilization in Thermophiles

Thermophilic organisms flourish in varied high-temperature environmental niches that are deadly to other organisms. Recently, genomic evidence has implicated a critical role for disulfide bonds in the structural stabilization of intracellular proteins from certain of these organisms, contrary to the conventional view that structural disulfide bonds are exclusively extracellular. Here both computational and structural data are presented to explore the occurrence of disulfide bonds as a protein-stabilization method across many thermophilic prokaryotes. Based on computational studies, disulfide-bond richness is found to be widespread, with thermophiles containing the highest levels. Interestingly, only a distinct subset of thermophiles exhibit this property. A computational search for proteins matching this target phylogenetic profile singles out a specific protein, known as protein disulfide oxidoreductase, as a potential key player in thermophilic intracellular disulfide-bond formation. Finally, biochemical support in the form of a new crystal structure of a thermophilic protein with three disulfide bonds is presented together with a survey of known structures from the literature. Together, the results provide insight into biochemical specialization and the diversity of methods employed by organisms to stabilize their proteins in exotic environments. The findings also motivate continued efforts to sequence genomes from divergent organisms

Age, extent and carbon storage of the central Congo Basin peatland complex

Peatlands are carbon-rich ecosystems that cover just three per cent of Earth's land surface, but store one-third of soil carbon. Peat soils are formed by the build-up of partially decomposed organic matter under waterlogged anoxic conditions. Most peat is found in cool climatic regions where unimpeded decomposition is slower, but deposits are also found under some tropical swamp forests. Here we present field measurements from one of the world's most extensive regions of swamp forest, the Cuvette Centrale depression in the central Congo Basin. We find extensive peat deposits beneath the swamp forest vegetation (peat defined as material with an organic matter content of at least 65 per cent to a depth of at least 0.3 metres). Radiocarbon dates indicate that peat began accumulating from about 10,600 years ago, coincident with the onset of more humid conditions in central Africa at the beginning of the Holocene. The peatlands occupy large interfluvial basins, and seem to be largely rain-fed and ombrotrophic-like (of low nutrient status) systems. Although the peat layer is relatively shallow (with a maximum depth of 5.9 metres and a median depth of 2.0 metres), by combining in situ and remotely sensed data, we estimate the area of peat to be approximately 145,500 square kilometres (95 per cent confidence interval of 131,900-156,400 square kilometres), making the Cuvette Centrale the most extensive peatland complex in the tropics. This area is more than five times the maximum possible area reported for the Congo Basin in a recent synthesis of pantropical peat extent. We estimate that the peatlands store approximately 30.6 petagrams (30.6 × 10(15) grams) of carbon belowground (95 per cent confidence interval of 6.3-46.8 petagrams of carbon)-a quantity that is similar to the above-ground carbon stocks of the tropical forests of the entire Congo Basin. Our result for the Cuvette Centrale increases the best estimate of global tropical peatland carbon stocks by 36 per cent, to 104.7 petagrams of carbon (minimum estimate of 69.6 petagrams of carbon; maximum estimate of 129.8 petagrams of carbon). This stored carbon is vulnerable to land-use change and any future reduction in precipitation

A summer heat wave decreases the immunocompetence of the mesograzer, Idotea baltica

Extreme events associated with global change will impose increasing stress on coastal organisms. How strong biological interactions such as the host–parasite arms-race are modulated by environmental change is largely unknown. The immune system of invertebrates, in particular phagocytosis and phenoloxidase activity response are key defence mechanisms against parasites, yet they may be sensitive to environmental perturbations. We here simulated an extreme event that mimicked the European heat wave in 2003 to investigate the effect of environmental change on the immunocompetence of the mesograzer Idotea baltica. Unlike earlier studies, our experiment aimed at simulation of the natural situation as closely as possible by using long acclimation, a slow increase in temperature and a natural community setting including the animals’ providence with natural food sources (Zostera marina and Fucus vesiculosus). Our results demonstrate that a simulated heat wave results in decreased immunocompetence of the mesograzer Idotea baltica, in particular a drop of phagocytosis by 50%. This suggests that global change has the potential to significantly affect host–parasite interactions

Connexin Mediated Cataract Prevention in Mice

Cataracts, named for any opacity in the ocular lens, remain the leading cause of vision loss in the world. Non-surgical methods for cataract prevention are still elusive. We have genetically tested whether enhanced lens gap junction communication, provided by increased α3 connexin (Cx46) proteins expressed from α8(Kiα3) knock-in alleles in Gja8tm1(Gja3)Tww mice, could prevent nuclear cataracts caused by the γB-crystallin S11R mutation in CrygbS11R/S11R mice. Remarkably, homozygous knock-in α8(Kiα3/Kiα3) mice fully prevented nuclear cataracts, while single knock-in α8(Kiα3/−) allele mice showed variable suppression of nuclear opacities in CrygbS11R/S11R mutant mice. Cataract prevention was correlated with the suppression of many pathological processes, including crystallin degradation and fiber cell degeneration, as well as preservation of normal calcium levels and stable actin filaments in the lens. This work demonstrates that enhanced intercellular gap junction communication can effectively prevent or delay nuclear cataract formation and suggests that small metabolites transported through gap junction channels protect the stability of crystallin proteins and the cytoskeletal structures in the lens core. Thus, the use of an array of small molecules to promote lens homeostasis may become a feasible non-surgical approach for nuclear cataract prevention in the future