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Stuart A. MacGowan Fbio Madeira Thiago Britto‐Borges Mateusz Warowny Alexey Drozdetskiy James B. Procter Geoffrey J. Barton 《Protein science : a publication of the Protein Society》2020,29(1):277-297
The Dundee Resource for Sequence Analysis and Structure Prediction (DRSASP; http://www.compbio.dundee.ac.uk/drsasp.html ) is a collection of web services provided by the Barton Group at the University of Dundee. DRSASP's flagship services are the JPred4 webserver for secondary structure and solvent accessibility prediction and the JABAWS 2.2 webserver for multiple sequence alignment, disorder prediction, amino acid conservation calculations, and specificity‐determining site prediction. DRSASP resources are available through conventional web interfaces and APIs but are also integrated into the Jalview sequence analysis workbench, which enables the composition of multitool interactive workflows. Other existing Barton Group tools are being brought under the banner of DRSASP, including NoD (Nucleolar localization sequence detector) and 14‐3‐3‐Pred. New resources are being developed that enable the analysis of population genetic data in evolutionary and 3D structural contexts. Existing resources are actively developed to exploit new technologies and maintain parity with evolving web standards. DRSASP provides substantial computational resources for public use, and since 2016 DRSASP services have completed over 1.5 million jobs. 相似文献
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A new theoretical survey of proteins'' resistance to constant speed stretching is performed for a set of 17 134 proteins as described by a structure-based model. The proteins selected have no gaps in their structure determination and consist of no more than 250 amino acids. Our previous studies have dealt with 7510 proteins of no more than 150 amino acids. The proteins are ranked according to the strength of the resistance. Most of the predicted top-strength proteins have not yet been studied experimentally. Architectures and folds which are likely to yield large forces are identified. New types of potent force clamps are discovered. They involve disulphide bridges and, in particular, cysteine slipknots. An effective energy parameter of the model is estimated by comparing the theoretical data on characteristic forces to the corresponding experimental values combined with an extrapolation of the theoretical data to the experimental pulling speeds. These studies provide guidance for future experiments on single molecule manipulation and should lead to selection of proteins for applications. A new class of proteins, involving cystein slipknots, is identified as one that is expected to lead to the strongest force clamps known. This class is characterized through molecular dynamics simulations. 相似文献
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Jaroslav Slamecka Steven McClellan Anna Wilk Javier Laurini Elizabeth Manci Simon P Hoerstrup 《Cell cycle (Georgetown, Tex.)》2018,17(3):330-347
Fetal stem cells are a unique type of adult stem cells that have been suggested to be broadly multipotent with some features of pluripotency. Their clinical potential has been documented but their upgrade to full pluripotency could open up a wide range of cell-based therapies particularly suited for pediatric tissue engineering, longitudinal studies or disease modeling. Here we describe episomal reprogramming of mesenchymal stem cells from the human amnion to pluripotency (AM-iPSC) in chemically defined conditions. The AM-iPSC expressed markers of embryonic stem cells, readily formed teratomas with tissues of all three germ layers present and had a normal karyotype after around 40 passages in culture. We employed novel computational methods to determine the degree of pluripotency from microarray and RNA sequencing data in these novel lines alongside an iPSC and ESC control and found that all lines were deemed pluripotent, however, with variable scores. Differential expression analysis then identified several groups of genes that potentially regulate this variability in lines within the boundaries of pluripotency, including metallothionein proteins. By further studying this variability, characteristics relevant to cell-based therapies, like differentiation propensity, could be uncovered and predicted in the pluripotent stage. 相似文献
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