Journal Articles

Evidence for Functionally Relevant Encounter Complexes in Nitrogenase Catalysis

Journal of American Chemical Society - Thu, 09/24/2015 - 14:27

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b08310
Categories: Journal Articles

In Situ Probing of the Active Site Geometry of Ultrathin Nanowires for the Oxygen Reduction Reaction

Journal of American Chemical Society - Thu, 09/24/2015 - 14:27

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b07093
Categories: Journal Articles

Sulfur-Bridged Terthiophene Dimers: How Sulfur Oxidation State Controls Interchromophore Electronic Coupling

Journal of American Chemical Society - Thu, 09/24/2015 - 10:31

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b05457
Categories: Journal Articles

Barrierless Photoisomerization of 11-cis Retinal Protonated Schiff Base in Solution

Journal of American Chemical Society - Thu, 09/24/2015 - 08:44

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b06492
Categories: Journal Articles

Systematic noise degrades gene co-expression signals but can be corrected

BMC Bioinformatics - Thu, 09/24/2015 - 07:00
Background: In the past decade, the identification of gene co-expression has become a routine part of the analysis of high-dimensional microarray data. Gene co-expression, which is mostly detected via the Pearson correlation coefficient, has played an important role in the discovery of molecular pathways and networks. Unfortunately, the presence of systematic noise in high-dimensional microarray datasets corrupts estimates of gene co-expression. Removing systematic noise from microarray data is therefore crucial. Many cleaning approaches for microarray data exist, however these methods are aimed towards improving differential expression analysis and their performances have been primarily tested for this application. To our knowledge, the performances of these approaches have never been systematically compared in the context of gene co-expression estimation. Results: Using simulations we demonstrate that standard cleaning procedures, such as background correction and quantile normalization, fail to adequately remove systematic noise that affects gene co-expression and at times further degrade true gene co-expression. Instead we show that a global version of removal of unwanted variation (RUV), a data-driven approach, removes systematic noise but also allows the estimation of the true underlying gene-gene correlations. We compare the performance of all noise removal methods when applied to five large published datasets on gene expression in the human brain. RUV retrieves the highest gene co-expression values for sets of genes known to interact, but also provides the greatest consistency across all five datasets. We apply the method to prioritize epileptic encephalopathy candidate genes. Conclusions: Our work raises serious concerns about the quality of many published gene co-expression analyses. RUV provides an efficient and flexible way to remove systematic noise from high-dimensional microarray datasets when the objective is gene co-expression analysis. The RUV method as applicable in the context of gene-gene correlation estimation is available as a BioconductoR-package: RUVcorr.
Categories: Journal Articles

2D and 3D similarity landscape analysis identifies PARP as a novel off-target for the drug Vatalanib

BMC Bioinformatics - Thu, 09/24/2015 - 07:00
Background: Searching for two-dimensional (2D) structural similarities is a useful tool to identify new active compounds in drug-discovery programs. However, as 2D similarity measures neglect important structural and functional features, similarity by 2D might be underestimated. In the present study, we used combined 2D and three-dimensional (3D) similarity comparisons to reveal possible new functions and/or side-effects of known bioactive compounds. Results: We utilised more than 10,000 compounds from the SuperTarget database with known inhibition values for twelve different anti-cancer targets. We performed all-against-all comparisons resulting in 2D similarity landscapes. Among the regions with low 2D similarity scores are inhibitors of vascular endothelial growth factor receptor (VEGFR) and inhibitors of poly ADP-ribose polymerase (PARP). To demonstrate that 3D landscape comparison can identify similarities, which are untraceable in 2D similarity comparisons, we analysed this region in more detail. This 3D analysis showed the unexpected structural similarity between inhibitors of VEGFR and inhibitors of PARP. Among the VEGFR inhibitors that show similarities to PARP inhibitors was Vatalanib, an oral “multi-targeted” small molecule protein kinase inhibitor being studied in phase-III clinical trials in cancer therapy. An in silico docking simulation and an in vitro HT universal colorimetric PARP assay confirmed that the VEGFR inhibitor Vatalanib exhibits off-target activity as a PARP inhibitor, broadening its mode of action. Conclusion: In contrast to the 2D-similarity search, the 3D-similarity landscape comparison identifies new functions and side effects of the known VEGFR inhibitor Vatalanib.
Categories: Journal Articles

STAP cells are derived from ES cells

Nature - Wed, 09/23/2015 - 23:00

STAP cells are derived from ES cells

Nature 525, 7570 (2015). doi:10.1038/nature15366

Authors: Daijiro Konno, Takeya Kasukawa, Kosuke Hashimoto, Takehiko Itoh, Taeko Suetsugu, Ikuo Miura, Shigeharu Wakana, Piero Carninci & Fumio Matsuzaki

arising fromH. Obokata et al.Nature505, 641–647 (2014) doi:10.1038/nature12968; retraction 511, 112 (2014) doi:10.1038/nature13598; and H. Obokata et al.Nature505, 676–680 (2014)

Categories: Journal Articles

Failure to replicate the STAP cell phenomenon

Nature - Wed, 09/23/2015 - 23:00

Failure to replicate the STAP cell phenomenon

Nature 525, 7570 (2015). doi:10.1038/nature15513

Authors: Alejandro De Los Angeles, Francesco Ferrari, Yuko Fujiwara, Ronald Mathieu, Soohyun Lee, Semin Lee, Ho-Chou Tu, Samantha Ross, Stephanie Chou, Minh Nguyen, Zhaoting Wu, Thorold W. Theunissen, Benjamin E. Powell, Sumeth Imsoonthornruksa, Jiekai Chen, Marti Borkent, Vladislav Krupalnik, Ernesto Lujan, Marius Wernig, Jacob H. Hanna, Konrad Hochedlinger, Duanqing Pei, Rudolf Jaenisch, Hongkui Deng, Stuart H. Orkin, Peter J. Park & George Q. Daley

arising from H. Obokata et al.Nature505, 641–647 (2014) doi:10.1038/nature12968; retraction 511, 112 (2014) doi:10.1038/nature13598; and H. Obokata et al.Nature505, 676–680 (2014

Categories: Journal Articles

The diurnal cycle of water ice on comet 67P/Churyumov–Gerasimenko

Nature - Wed, 09/23/2015 - 23:00

The diurnal cycle of water ice on comet 67P/Churyumov–Gerasimenko

Nature 525, 7570 (2015). doi:10.1038/nature14869

Authors: M. C. De Sanctis, F. Capaccioni, M. Ciarniello, G. Filacchione, M. Formisano, S. Mottola, A. Raponi, F. Tosi, D. Bockelée-Morvan, S. Erard, C. Leyrat, B. Schmitt, E. Ammannito, G. Arnold, M. A. Barucci, M. Combi, M. T. Capria, P. Cerroni, W.-H. Ip, E. Kuehrt, T. B. McCord, E. Palomba, P. Beck & E. Quirico

Observations of cometary nuclei have revealed a very limited amount of surface water ice, which is insufficient to explain the observed water outgassing. This was clearly demonstrated on comet 9P/Tempel 1, where the dust jets (driven by volatiles) were only partially correlated with the exposed ice regions. The observations of 67P/Churyumov–Gerasimenko have revealed that activity has a diurnal variation in intensity arising from changing insolation conditions. It was previously concluded that water vapour was generated in ice-rich subsurface layers with a transport mechanism linked to solar illumination, but that has not hitherto been observed. Periodic condensations of water vapour very close to, or on, the surface were suggested to explain short-lived outbursts seen near sunrise on comet 9P/Tempel 1. Here we report observations of water ice on the surface of comet 67P/Churyumov–Gerasimenko, appearing and disappearing in a cyclic pattern that follows local illumination conditions, providing a source of localized activity. This water cycle appears to be an important process in the evolution of the comet, leading to cyclical modification of the relative abundance of water ice on its surface.

Categories: Journal Articles

htsint: a Python library for sequencing pipelines that combines data through gene set generation

BMC Bioinformatics - Wed, 09/23/2015 - 19:00
Background: Sequencing technologies provide a wealth of details in terms of genes, expression, splice variants, polymorphisms, and other features. A standard for sequencing analysis pipelines is to put genomic or transcriptomic features into a context of known functional information, but the relationships between ontology terms are often ignored. For RNA-Seq, considering genes and their genetic variants at the group level enables a convenient way to both integrate annotation data and detect small coordinated changes between experimental conditions, a known caveat of gene level analyses. Results: We introduce the high throughput data integration tool, htsint, as an extension to the commonly used gene set enrichment frameworks. The central aim of htsint is to compile annotation information from one or more taxa in order to calculate functional distances among all genes in a specified gene space. Spectral clustering is then used to partition the genes, thereby generating functional modules. The gene space can range from a targeted list of genes, like a specific pathway, all the way to an ensemble of genomes. Given a collection of gene sets and a count matrix of transcriptomic features (e.g. expression, polymorphisms), the gene sets produced by htsint can be tested for ‘enrichment’ or conditional differences using one of a number of commonly available packages. Conclusion: The database and bundled tools to generate functional modules were designed with sequencing pipelines in mind, but the toolkit nature of htsint allows it to also be used in other areas of genomics. The software is freely available as a Python library through GitHub at https://github.com/ajrichards/htsint.
Categories: Journal Articles

Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity

PLoS Computational Biology - Wed, 09/23/2015 - 16:00

by Noah Ollikainen, René M. de Jong, Tanja Kortemme

Interactions between small molecules and proteins play critical roles in regulating and facilitating diverse biological functions, yet our ability to accurately re-engineer the specificity of these interactions using computational approaches has been limited. One main difficulty, in addition to inaccuracies in energy functions, is the exquisite sensitivity of protein–ligand interactions to subtle conformational changes, coupled with the computational problem of sampling the large conformational search space of degrees of freedom of ligands, amino acid side chains, and the protein backbone. Here, we describe two benchmarks for evaluating the accuracy of computational approaches for re-engineering protein-ligand interactions: (i) prediction of enzyme specificity altering mutations and (ii) prediction of sequence tolerance in ligand binding sites. After finding that current state-of-the-art “fixed backbone” design methods perform poorly on these tests, we develop a new “coupled moves” design method in the program Rosetta that couples changes to protein sequence with alterations in both protein side-chain and protein backbone conformations, and allows for changes in ligand rigid-body and torsion degrees of freedom. We show significantly increased accuracy in both predicting ligand specificity altering mutations and binding site sequences. These methodological improvements should be useful for many applications of protein – ligand design. The approach also provides insights into the role of subtle conformational adjustments that enable functional changes not only in engineering applications but also in natural protein evolution.
Categories: Journal Articles

Propensity of Hydrated Excess Protons and Hydroxide Anions for the Air–Water Interface

Journal of American Chemical Society - Wed, 09/23/2015 - 15:24

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b07232
Categories: Journal Articles
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