CiteULike: neils's design http://www.citeulike.org/user/neils/tag/design CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/neils/article/2568656 <i>Nature (19 March 2008)</i> Kemp elimination catalysts by computational enzyme design Daniela Röthlisberger Olga Khersonsky Andrew Wollacott Lin Jiang Jason Dechancie Jamie Betker Jasmine Gallaher Eric Althoff Alexandre Zanghellini Orly Dym Shira Albeck Kendall Houk Dan Tawfik David Baker doi:10.1038/nature06879 Nature (19 March 2008) 2008-03-21T04:33:18-00:00 Nature 0028-0836 Nature Publishing Group catalysis computational design enzyme http://www.citeulike.org/user/neils/article/2054458 <i>Genome Res, Vol. 12, No. 10. (Oct 2002), pp. 1611-1618.</i><br /><br />The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort. The Bioperl toolkit: Perl modules for the life sciences. Jason Stajich David Block Kris Boulez Steven Brenner Stephen Chervitz Chris Dagdigian Georg Fuellen James Gilbert Ian Korf Hilmar Lapp Heikki Lehväslaiho Chad Matsalla Chris Mungall Brian Osborne Matthew Pocock Peter Schattner Martin Senger Lincoln Stein Elia Stupka Mark Wilkinson Ewan Birney Genome Res, Vol. 12, No. 10. (Oct 2002), pp. 1611-1618. 2007-12-04T03:22:10-00:00 Genome Res 12 10 1611 1618 algorithms animals article-nar article-predikin biological biology computational computer database databases design genetic graphics humans integration internet management online perl sciences software systems http://www.citeulike.org/user/neils/article/2054454 <i>Curr Opin Struct Biol, Vol. 16, No. 6. (Dec 2006), pp. 676-685.</i><br /><br />To achieve high biological specificity, protein kinases and phosphatases often recognize their targets through interactions that occur outside of the active site. Although the role of modular protein-protein interaction domains in kinase and phosphatase signaling has been well characterized, it is becoming clear that many kinases and phosphatases utilize docking interactions - recognition of a short peptide motif in target partners by a groove on the catalytic domain that is separate from the active site. Docking is particularly prevalent in serine/threonine kinases and phosphatases, and is a versatile organizational tool for building complex signaling networks; it confers a high degree of specificity and, in some cases, allosteric regulation. Docking interactions in protein kinase and phosphatase networks. Attila Reményi Matthew Good Wendell Lim Curr Opin Struct Biol, Vol. 16, No. 6. (Dec 2006), pp. 676-685. 2007-12-04T03:22:10-00:00 Curr Opin Struct Biol 16 6 676 685 allosteric article-predikin binding biological complexes conformation design drug kinase kinases map models molecular multiprotein phosphatases phosphoprotein protein regulation signal signaling sites structure system tertiary transduction http://www.citeulike.org/user/neils/article/2054449 <i>Science, Vol. 303, No. 5665. (Mar 2004), pp. 1800-1805.</i><br /><br />Protein kinases are targets for treatment of a number of diseases. This review focuses on kinase inhibitors that are in the clinic or in clinical trials and for which structural information is available. Structures have informed drug design and have illuminated the mechanism of inhibition. We review progress with the receptor tyrosine kinases (growth factor receptors EGFR, VEGFR, and FGFR) and nonreceptor tyrosine kinases (Bcr-Abl), where advances have been made with cancer therapeutic agents such as Herceptin and Gleevec. Among the serine-threonine kinases, p38, Rho-kinase, cyclin-dependent kinases, and Chk1 have been targeted with productive results for inflammation and cancer. Structures have provided insights into targeting the inactive or active form of the kinase, for targeting the global constellation of residues at the ATP site or less conserved additional pockets or single residues, and into targeting noncatalytic domains. Protein kinase inhibitors: insights into drug design from structure. Martin Noble Jane Endicott Louise Johnson Science, Vol. 303, No. 5665. (Mar 2004), pp. 1800-1805. 2007-12-04T03:22:10-00:00 Science 303 5665 1800 1805 adenosine agents antineoplastic article-predikin as binding catalytic clinical conformation design domain drug enzyme humans inhibitors kinase kinases models molecular protein relationship signal sites structure structure-activity tertiary topic transduction trials triphosphate http://www.citeulike.org/user/neils/article/2054439 <i>J Mol Biol, Vol. 305, No. 3. (Jan 2001), pp. 567-580.</i><br /><br />We describe and validate a new membrane protein topology prediction method, TMHMM, based on a hidden Markov model. We present a detailed analysis of TMHMM's performance, and show that it correctly predicts 97-98 \% of the transmembrane helices. Additionally, TMHMM can discriminate between soluble and membrane proteins with both specificity and sensitivity better than 99 \%, although the accuracy drops when signal peptides are present. This high degree of accuracy allowed us to predict reliably integral membrane proteins in a large collection of genomes. Based on these predictions, we estimate that 20-30 \% of all genes in most genomes encode membrane proteins, which is in agreement with previous estimates. We further discovered that proteins with N(in)-C(in) topologies are strongly preferred in all examined organisms, except Caenorhabditis elegans, where the large number of 7TM receptors increases the counts for N(out)-C(in) topologies. We discuss the possible relevance of this finding for our understanding of membrane protein assembly mechanisms. A TMHMM prediction service is available at http://www.cbs.dtu.dk/services/TMHMM/. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. A Krogh B Larsson G von Heijne EL Sonnhammer J Mol Biol, Vol. 305, No. 3. (Jan 2001), pp. 567-580. 2007-12-04T03:22:10-00:00 J Mol Biol 305 3 567 580 article-nar article-predikin bacterial chains computational databases design fungal genome internet markov membrane of plant porins protein proteins reproducibility research results secondary sensitivity signals software solubility sorting specificity structure http://www.citeulike.org/user/neils/article/2054420 <i>BMC Bioinformatics, Vol. 5 (Jun 2004)</i><br /><br />BACKGROUND: Post-translational phosphorylation is one of the most common protein modifications. Phosphoserine, threonine and tyrosine residues play critical roles in the regulation of many cellular processes. The fast growing number of research reports on protein phosphorylation points to a general need for an accurate database dedicated to phosphorylation to provide easily retrievable information on phosphoproteins. DESCRIPTION: Phospho.ELM http://phospho.elm.eu.org is a new resource containing experimentally verified phosphorylation sites manually curated from the literature and is developed as part of the ELM (Eukaryotic Linear Motif) resource. Phospho.ELM constitutes the largest searchable collection of phosphorylation sites available to the research community. The Phospho.ELM entries store information about substrate proteins with the exact positions of residues known to be phosphorylated by cellular kinases. Additional annotation includes literature references, subcellular compartment, tissue distribution, and information about the signaling pathways involved as well as links to the molecular interaction database MINT. Phospho.ELM version 2.0 contains 1703 phosphorylation site instances for 556 phosphorylated proteins. CONCLUSION: Phospho.ELM will be a valuable tool both for molecular biologists working on protein phosphorylation sites and for bioinformaticians developing computational predictions on the specificity of phosphorylation reactions. Phospho.ELM: a database of experimentally verified phosphorylation sites in eukaryotic proteins. Francesca Diella Scott Cameron Christine Gemünd Rune Linding Allegra Via Bernhard Kuster Thomas Pontén Nikolaj Blom Toby Gibson BMC Bioinformatics, Vol. 5 (Jun 2004) 2007-12-04T03:22:09-00:00 BMC Bioinformatics 5 animals article-predikin binding databases design humans mice phosphorylation post-translational processing protein proteins rats research sites software