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Wilkinson P, Sengerova J, Matteoni R, Chen CK, Soulat G, Ureta-Vidal A, Fessele S, Hagn M, Massimi M, Pickford K, Butler RH, Marschall S, Mallon AM, Pickard A, Raspa M, Scavizzi F, Fray M, Larrigaldie V, Leyritz J, Birney E, Tocchini-Valentini GP, Brown S, Herault Y, Montoliu L, de Angelis MH, Smedley D. EMMA--mouse mutant resources for the international scientific community. Nucleic Acids Res 2009; 38:D570-6. [PMID: 19783817 PMCID: PMC2808872 DOI: 10.1093/nar/gkp799] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The laboratory mouse is the premier animal model for studying human disease and thousands of mutants have been identified or produced, most recently through gene-specific mutagenesis approaches. High throughput strategies by the International Knockout Mouse Consortium (IKMC) are producing mutants for all protein coding genes. Generating a knock-out line involves huge monetary and time costs so capture of both the data describing each mutant alongside archiving of the line for distribution to future researchers is critical. The European Mouse Mutant Archive (EMMA) is a leading international network infrastructure for archiving and worldwide provision of mouse mutant strains. It operates in collaboration with the other members of the Federation of International Mouse Resources (FIMRe), EMMA being the European component. Additionally EMMA is one of four repositories involved in the IKMC, and therefore the current figure of 1700 archived lines will rise markedly. The EMMA database gathers and curates extensive data on each line and presents it through a user-friendly website. A BioMart interface allows advanced searching including integrated querying with other resources e.g. Ensembl. Other resources are able to display EMMA data by accessing our Distributed Annotation System server. EMMA database access is publicly available at http://www.emmanet.org.
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Affiliation(s)
- Phil Wilkinson
- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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52
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The evolution of protein functions and networks: a family-centric approach. Biochem Soc Trans 2009; 37:745-50. [PMID: 19614587 DOI: 10.1042/bst0370745] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The study of superfamilies of protein domains using a combination of structure, sequence and function data provides insights into deep evolutionary history. In the present paper, analyses of functional diversity within such superfamilies as defined in the CATH-Gene3D resource are described. These analyses focus on structure-function relationships in very large and diverse superfamilies, and on the evolution of domain superfamily members in protein-protein complexes.
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53
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Guex N, Peitsch MC, Schwede T. Automated comparative protein structure modeling with SWISS-MODEL and Swiss-PdbViewer: a historical perspective. Electrophoresis 2009; 30 Suppl 1:S162-73. [PMID: 19517507 DOI: 10.1002/elps.200900140] [Citation(s) in RCA: 1320] [Impact Index Per Article: 88.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
SWISS-MODEL pioneered the field of automated modeling as the first protein modeling service on the Internet. In combination with the visualization tool Swiss-PdbViewer, the Internet-based Workspace and the SWISS-MODEL Repository, it provides a fully integrated sequence to structure analysis and modeling platform. This computational environment is made freely available to the scientific community with the aim to hide the computational complexity of structural bioinformatics and encourage bench scientists to make use of the ever-increasing structural information available. Indeed, over the last decade, the availability of structural information has significantly increased for many organisms as a direct consequence of the complementary nature of comparative protein modeling and experimental structure determination. This has a very positive and enabling impact on many different applications in biomedical research as described in this paper.
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Affiliation(s)
- Nicolas Guex
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
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54
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Nicol JW, Helt GA, Blanchard SG, Raja A, Loraine AE. The Integrated Genome Browser: free software for distribution and exploration of genome-scale datasets. Bioinformatics 2009; 25:2730-1. [PMID: 19654113 PMCID: PMC2759552 DOI: 10.1093/bioinformatics/btp472] [Citation(s) in RCA: 476] [Impact Index Per Article: 31.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Summary: Experimental techniques that survey an entire genome demand flexible, highly interactive visualization tools that can display new data alongside foundation datasets, such as reference gene annotations. The Integrated Genome Browser (IGB) aims to meet this need. IGB is an open source, desktop graphical display tool implemented in Java that supports real-time zooming and panning through a genome; layout of genomic features and datasets in moveable, adjustable tiers; incremental or genome-scale data loading from remote web servers or local files; and dynamic manipulation of quantitative data via genome graphs. Availability: The application and source code are available from http://igb.bioviz.org and http://genoviz.sourceforge.net. Contact:aloraine@uncc.edu
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Affiliation(s)
- John W Nicol
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, North Carolina Research Campus, 600 Laureate Way, Kannapolis, NC 28081, USA
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55
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Zielinska DF, Gnad F, Jedrusik-Bode M, Wiśniewski JR, Mann M. Caenorhabditis elegans Has a Phosphoproteome Atypical for Metazoans That Is Enriched in Developmental and Sex Determination Proteins. J Proteome Res 2009; 8:4039-49. [DOI: 10.1021/pr900384k] [Citation(s) in RCA: 57] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Dorota F. Zielinska
- Department of Proteomics and Signal Transduction, Max-Planck-Institute for Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany, Department of Systems Biology, Harvard Medical School, 200 Longwood Avenue, Boston, Massachusetts 02115, and Laboratory of Chromatin Biochemistry, Max-Planck-Institute for Biophysical Chemistry, Am Faβberg 11, D-37077 Göttingen, Germany
| | - Florian Gnad
- Department of Proteomics and Signal Transduction, Max-Planck-Institute for Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany, Department of Systems Biology, Harvard Medical School, 200 Longwood Avenue, Boston, Massachusetts 02115, and Laboratory of Chromatin Biochemistry, Max-Planck-Institute for Biophysical Chemistry, Am Faβberg 11, D-37077 Göttingen, Germany
| | - Monika Jedrusik-Bode
- Department of Proteomics and Signal Transduction, Max-Planck-Institute for Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany, Department of Systems Biology, Harvard Medical School, 200 Longwood Avenue, Boston, Massachusetts 02115, and Laboratory of Chromatin Biochemistry, Max-Planck-Institute for Biophysical Chemistry, Am Faβberg 11, D-37077 Göttingen, Germany
| | - Jacek R. Wiśniewski
- Department of Proteomics and Signal Transduction, Max-Planck-Institute for Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany, Department of Systems Biology, Harvard Medical School, 200 Longwood Avenue, Boston, Massachusetts 02115, and Laboratory of Chromatin Biochemistry, Max-Planck-Institute for Biophysical Chemistry, Am Faβberg 11, D-37077 Göttingen, Germany
| | - Matthias Mann
- Department of Proteomics and Signal Transduction, Max-Planck-Institute for Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany, Department of Systems Biology, Harvard Medical School, 200 Longwood Avenue, Boston, Massachusetts 02115, and Laboratory of Chromatin Biochemistry, Max-Planck-Institute for Biophysical Chemistry, Am Faβberg 11, D-37077 Göttingen, Germany
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Blankenburg H, Finn RD, Prlić A, Jenkinson AM, Ramírez F, Emig D, Schelhorn SE, Büch J, Lengauer T, Albrecht M. DASMI: exchanging, annotating and assessing molecular interaction data. ACTA ACUST UNITED AC 2009; 25:1321-8. [PMID: 19420069 PMCID: PMC2677739 DOI: 10.1093/bioinformatics/btp142] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
MOTIVATION Ever increasing amounts of biological interaction data are being accumulated worldwide, but they are currently not readily accessible to the biologist at a single site. New techniques are required for retrieving, sharing and presenting data spread over the Internet. RESULTS We introduce the DASMI system for the dynamic exchange, annotation and assessment of molecular interaction data. DASMI is based on the widely used Distributed Annotation System (DAS) and consists of a data exchange specification, web servers for providing the interaction data and clients for data integration and visualization. The decentralized architecture of DASMI affords the online retrieval of the most recent data from distributed sources and databases. DASMI can also be extended easily by adding new data sources and clients. We describe all DASMI components and demonstrate their use for protein and domain interactions. AVAILABILITY The DASMI tools are available at http://www.dasmi.de/ and http://ipfam.sanger.ac.uk/graph. The DAS registry and the DAS 1.53E specification is found at http://www.dasregistry.org/.
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Affiliation(s)
- Hagen Blankenburg
- Max Planck Institute for Informatics, Campus E 1.4, 66123 Saarbrücken, Germany
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57
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Barrio AM, Lagercrantz E, Sperber GO, Blomberg J, Bongcam-Rudloff E. Annotation and visualization of endogenous retroviral sequences using the Distributed Annotation System (DAS) and eBioX. BMC Bioinformatics 2009; 10 Suppl 6:S18. [PMID: 19534743 PMCID: PMC2697641 DOI: 10.1186/1471-2105-10-s6-s18] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Background The Distributed Annotation System (DAS) is a widely used network protocol for sharing biological information. The distributed aspects of the protocol enable the use of various reference and annotation servers for connecting biological sequence data to pertinent annotations in order to depict an integrated view of the data for the final user. Results An annotation server has been devised to provide information about the endogenous retroviruses detected and annotated by a specialized in silico tool called RetroTector. We describe the procedure to implement the DAS 1.5 protocol commands necessary for constructing the DAS annotation server. We use our server to exemplify those steps. Data distribution is kept separated from visualization which is carried out by eBioX, an easy to use open source program incorporating multiple bioinformatics utilities. Some well characterized endogenous retroviruses are shown in two different DAS clients. A rapid analysis of areas free from retroviral insertions could be facilitated by our annotations. Conclusion The DAS protocol has shown to be advantageous in the distribution of endogenous retrovirus data. The distributed nature of the protocol is also found to aid in combining annotation and visualization along a genome in order to enhance the understanding of ERV contribution to its evolution. Reference and annotation servers are conjointly used by eBioX to provide visualization of ERV annotations as well as other data sources. Our DAS data source can be found in the central public DAS service repository, , or at .
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Affiliation(s)
- Alvaro Martínez Barrio
- The Linnaeus Centre for Bioinformatics, Uppsala University, Biomedical centre, P,O, Box 598, SE-75124 Uppsala, Sweden.
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58
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Blankenburg H, Ramírez F, Büch J, Albrecht M. DASMIweb: online integration, analysis and assessment of distributed protein interaction data. Nucleic Acids Res 2009; 37:W122-8. [PMID: 19502495 PMCID: PMC2703953 DOI: 10.1093/nar/gkp438] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
In recent years, we have witnessed a substantial increase of the amount of available protein interaction data. However, most data are currently not readily accessible to the biologist at a single site, but scattered over multiple online repositories. Therefore, we have developed the DASMIweb server that affords the integration, analysis and qualitative assessment of distributed sources of interaction data in a dynamic fashion. Since DASMIweb allows for querying many different resources of protein and domain interactions simultaneously, it serves as an important starting point for interactome studies and assists the user in finding publicly accessible interaction data with minimal effort. The pool of queried resources is fully configurable and supports the inclusion of own interaction data or confidence scores. In particular, DASMIweb integrates confidence measures like functional similarity scores to assess individual interactions. The retrieved results can be exported in different file formats like MITAB or SIF. DASMIweb is freely available at http://www.dasmiweb.de.
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Affiliation(s)
- Hagen Blankenburg
- Max Planck Institute for Informatics, Campus E1.4, 66123 Saarbrücken, Germany.
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59
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Sadowski MI, Jones DT. The sequence-structure relationship and protein function prediction. Curr Opin Struct Biol 2009; 19:357-62. [PMID: 19406632 DOI: 10.1016/j.sbi.2009.03.008] [Citation(s) in RCA: 66] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2009] [Accepted: 03/16/2009] [Indexed: 11/28/2022]
Abstract
An incomplete understanding of protein sequence/structure/function relationships causes many difficulties for prediction methods. The highly complex nature of these relationships is a consequence of the interplay between physics and evolution that has been studied using a wide array of experimental and theoretical techniques. We review recent findings relating to conservation of sequence, structure and function and discuss their use in developing improved prediction methods.
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Affiliation(s)
- M I Sadowski
- Division of Mathematical Biology, National Institute for Medical Research, The Ridgeway, Mill Hill, London NW7 1AA UK
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60
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Messina DN, Sonnhammer ELL. DASher: a stand-alone protein sequence client for DAS, the Distributed Annotation System. ACTA ACUST UNITED AC 2009; 25:1333-4. [PMID: 19297349 DOI: 10.1093/bioinformatics/btp153] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
SUMMARY The rise in biological sequence data has led to a proliferation of separate, specialized databases. While there is great value in having many independent annotations, it is critical that there be a way to integrate them in one combined view. The Distributed Annotation System (DAS) was developed for that very purpose. There are currently no DAS clients that are open source, specialized for aggregating and comparing protein sequence annotation, and that can run as a self-contained application outside of a web browser. The speed, flexibility and extensibility that come with a stand-alone application motivated us to create DASher, an open-source Java DAS client. Given a UniProt sequence identifier, DASher automatically queries DAS-supporting servers worldwide for any information on that sequence and then displays the annotations in an interactive viewer for easy comparison. DASher is a fast, Java-based DAS client optimized for viewing protein sequence annotation and compliant with the latest DAS protocol specification 1.53E. AVAILABILITY DASher is available for direct use and download at http://dasher.sbc.su.se including examples and source code under the GPLv3 licence. Java version 6 or higher is required.
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Affiliation(s)
- David N Messina
- Stockholm Bioinformatics Centre, Stockholm University, 10691 Stockholm, Sweden
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61
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Arnold K, Kiefer F, Kopp J, Battey JND, Podvinec M, Westbrook JD, Berman HM, Bordoli L, Schwede T. The Protein Model Portal. JOURNAL OF STRUCTURAL AND FUNCTIONAL GENOMICS 2009; 10:1-8. [PMID: 19037750 PMCID: PMC2704613 DOI: 10.1007/s10969-008-9048-5] [Citation(s) in RCA: 117] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2008] [Accepted: 11/02/2008] [Indexed: 11/28/2022]
Abstract
Structural Genomics has been successful in determining the structures of many unique proteins in a high throughput manner. Still, the number of known protein sequences is much larger than the number of experimentally solved protein structures. Homology (or comparative) modeling methods make use of experimental protein structures to build models for evolutionary related proteins. Thereby, experimental structure determination efforts and homology modeling complement each other in the exploration of the protein structure space. One of the challenges in using model information effectively has been to access all models available for a specific protein in heterogeneous formats at different sites using various incompatible accession code systems. Often, structure models for hundreds of proteins can be derived from a given experimentally determined structure, using a variety of established methods. This has been done by all of the PSI centers, and by various independent modeling groups. The goal of the Protein Model Portal (PMP) is to provide a single portal which gives access to the various models that can be leveraged from PSI targets and other experimental protein structures. A single interface allows all existing pre-computed models across these various sites to be queried simultaneously, and provides links to interactive services for template selection, target-template alignment, model building, and quality assessment. The current release of the portal consists of 7.6 million model structures provided by different partner resources (CSMP, JCSG, MCSG, NESG, NYSGXRC, JCMM, ModBase, SWISS-MODEL Repository). The PMP is available at http://www.proteinmodelportal.org and from the PSI Structural Genomics Knowledgebase.
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Affiliation(s)
- Konstantin Arnold
- Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH-4056 Basel, Switzerland
- Swiss Institute of Bioinformatics (SIB), Basel, Switzerland
| | - Florian Kiefer
- Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH-4056 Basel, Switzerland
- Swiss Institute of Bioinformatics (SIB), Basel, Switzerland
| | - Jürgen Kopp
- Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH-4056 Basel, Switzerland
- Swiss Institute of Bioinformatics (SIB), Basel, Switzerland
| | - James N. D. Battey
- Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH-4056 Basel, Switzerland
- Swiss Institute of Bioinformatics (SIB), Basel, Switzerland
| | - Michael Podvinec
- Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH-4056 Basel, Switzerland
- Swiss Institute of Bioinformatics (SIB), Basel, Switzerland
| | - John D. Westbrook
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854-8087 USA
| | - Helen M. Berman
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854-8087 USA
| | - Lorenza Bordoli
- Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH-4056 Basel, Switzerland
- Swiss Institute of Bioinformatics (SIB), Basel, Switzerland
| | - Torsten Schwede
- Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH-4056 Basel, Switzerland
- Swiss Institute of Bioinformatics (SIB), Basel, Switzerland
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62
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Abstract
The BioSapiens network has developed a distributed infrastructure for genome and proteome annotation
by laboratories anywhere in the world. The BioSapiens network has developed a distributed infrastructure for genome and proteome annotation by laboratories anywhere in the world.
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63
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Kell DB. Iron behaving badly: inappropriate iron chelation as a major contributor to the aetiology of vascular and other progressive inflammatory and degenerative diseases. BMC Med Genomics 2009; 2:2. [PMID: 19133145 PMCID: PMC2672098 DOI: 10.1186/1755-8794-2-2] [Citation(s) in RCA: 372] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2008] [Accepted: 01/08/2009] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular 'reactive oxygen species' (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. REVIEW We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation).The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible.This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, since in some circumstances (especially the presence of poorly liganded iron) molecules that are nominally antioxidants can actually act as pro-oxidants. The reduction of redox stress thus requires suitable levels of both antioxidants and effective iron chelators. Some polyphenolic antioxidants may serve both roles.Understanding the exact speciation and liganding of iron in all its states is thus crucial to separating its various pro- and anti-inflammatory activities. Redox stress, innate immunity and pro- (and some anti-)inflammatory cytokines are linked in particular via signalling pathways involving NF-kappaB and p38, with the oxidative roles of iron here seemingly involved upstream of the IkappaB kinase (IKK) reaction. In a number of cases it is possible to identify mechanisms by which ROSs and poorly liganded iron act synergistically and autocatalytically, leading to 'runaway' reactions that are hard to control unless one tackles multiple sites of action simultaneously. Some molecules such as statins and erythropoietin, not traditionally associated with anti-inflammatory activity, do indeed have 'pleiotropic' anti-inflammatory effects that may be of benefit here. CONCLUSION Overall we argue, by synthesising a widely dispersed literature, that the role of poorly liganded iron has been rather underappreciated in the past, and that in combination with peroxide and superoxide its activity underpins the behaviour of a great many physiological processes that degrade over time. Understanding these requires an integrative, systems-level approach that may lead to novel therapeutic targets.
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Affiliation(s)
- Douglas B Kell
- School of Chemistry and Manchester Interdisciplinary Biocentre, The University of Manchester, 131 Princess St, Manchester, M1 7DN, UK.
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64
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Kiefer F, Arnold K, Künzli M, Bordoli L, Schwede T. The SWISS-MODEL Repository and associated resources. Nucleic Acids Res 2009; 37:D387-92. [PMID: 18931379 PMCID: PMC2686475 DOI: 10.1093/nar/gkn750] [Citation(s) in RCA: 1570] [Impact Index Per Article: 104.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2008] [Accepted: 10/05/2008] [Indexed: 12/12/2022] Open
Abstract
SWISS-MODEL Repository (http://swissmodel.expasy.org/repository/) is a database of 3D protein structure models generated by the SWISS-MODEL homology-modelling pipeline. The aim of the SWISS-MODEL Repository is to provide access to an up-to-date collection of annotated 3D protein models generated by automated homology modelling for all sequences in Swiss-Prot and for relevant models organisms. Regular updates ensure that target coverage is complete, that models are built using the most recent sequence and template structure databases, and that improvements in the underlying modelling pipeline are fully utilised. As of September 2008, the database contains 3.4 million entries for 2.7 million different protein sequences from the UniProt database. SWISS-MODEL Repository allows the users to assess the quality of the models in the database, search for alternative template structures, and to build models interactively via SWISS-MODEL Workspace (http://swissmodel.expasy.org/workspace/). Annotation of models with functional information and cross-linking with other databases such as the Protein Model Portal (http://www.proteinmodelportal.org) of the PSI Structural Genomics Knowledge Base facilitates the navigation between protein sequence and structure resources.
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Affiliation(s)
- Florian Kiefer
- Biozentrum, University of Basel and SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Konstantin Arnold
- Biozentrum, University of Basel and SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Michael Künzli
- Biozentrum, University of Basel and SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Lorenza Bordoli
- Biozentrum, University of Basel and SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Torsten Schwede
- Biozentrum, University of Basel and SIB Swiss Institute of Bioinformatics, Basel, Switzerland
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65
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Hubbard TJP, Aken BL, Ayling S, Ballester B, Beal K, Bragin E, Brent S, Chen Y, Clapham P, Clarke L, Coates G, Fairley S, Fitzgerald S, Fernandez-Banet J, Gordon L, Graf S, Haider S, Hammond M, Holland R, Howe K, Jenkinson A, Johnson N, Kahari A, Keefe D, Keenan S, Kinsella R, Kokocinski F, Kulesha E, Lawson D, Longden I, Megy K, Meidl P, Overduin B, Parker A, Pritchard B, Rios D, Schuster M, Slater G, Smedley D, Spooner W, Spudich G, Trevanion S, Vilella A, Vogel J, White S, Wilder S, Zadissa A, Birney E, Cunningham F, Curwen V, Durbin R, Fernandez-Suarez XM, Herrero J, Kasprzyk A, Proctor G, Smith J, Searle S, Flicek P. Ensembl 2009. Nucleic Acids Res 2008; 37:D690-7. [PMID: 19033362 PMCID: PMC2686571 DOI: 10.1093/nar/gkn828] [Citation(s) in RCA: 683] [Impact Index Per Article: 42.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The Ensembl project (http://www.ensembl.org) is a comprehensive genome information system featuring an integrated set of genome annotation, databases, and other information for chordate, selected model organism and disease vector genomes. As of release 51 (November 2008), Ensembl fully supports 45 species, and three additional species have preliminary support. New species in the past year include orangutan and six additional low coverage mammalian genomes. Major additions and improvements to Ensembl since our previous report include a major redesign of our website; generation of multiple genome alignments and ancestral sequences using the new Enredo-Pecan-Ortheus pipeline and development of our software infrastructure, particularly to support the Ensembl Genomes project (http://www.ensemblgenomes.org/).
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Affiliation(s)
- T J P Hubbard
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
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66
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Lawson D, Arensburger P, Atkinson P, Besansky NJ, Bruggner RV, Butler R, Campbell KS, Christophides GK, Christley S, Dialynas E, Hammond M, Hill CA, Konopinski N, Lobo NF, MacCallum RM, Madey G, Megy K, Meyer J, Redmond S, Severson DW, Stinson EO, Topalis P, Birney E, Gelbart WM, Kafatos FC, Louis C, Collins FH. VectorBase: a data resource for invertebrate vector genomics. Nucleic Acids Res 2008; 37:D583-7. [PMID: 19028744 PMCID: PMC2686483 DOI: 10.1093/nar/gkn857] [Citation(s) in RCA: 185] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
VectorBase (http://www.vectorbase.org) is an NIAID-funded Bioinformatic Resource Center focused on invertebrate vectors of human pathogens. VectorBase annotates and curates vector genomes providing a web accessible integrated resource for the research community. Currently, VectorBase contains genome information for three mosquito species: Aedes aegypti, Anopheles gambiae and Culex quinquefasciatus, a body louse Pediculus humanus and a tick species Ixodes scapularis. Since our last report VectorBase has initiated a community annotation system, a microarray and gene expression repository and controlled vocabularies for anatomy and insecticide resistance. We have continued to develop both the software infrastructure and tools for interrogating the stored data.
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Affiliation(s)
- Daniel Lawson
- European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK.
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Gardner PP, Daub J, Tate JG, Nawrocki EP, Kolbe DL, Lindgreen S, Wilkinson AC, Finn RD, Griffiths-Jones S, Eddy SR, Bateman A. Rfam: updates to the RNA families database. Nucleic Acids Res 2008; 37:D136-40. [PMID: 18953034 PMCID: PMC2686503 DOI: 10.1093/nar/gkn766] [Citation(s) in RCA: 699] [Impact Index Per Article: 43.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Rfam is a collection of RNA sequence families, represented by multiple sequence alignments and covariance models (CMs). The primary aim of Rfam is to annotate new members of known RNA families on nucleotide sequences, particularly complete genomes, using sensitive BLAST filters in combination with CMs. A minority of families with a very broad taxonomic range (e.g. tRNA and rRNA) provide the majority of the sequence annotations, whilst the majority of Rfam families (e.g. snoRNAs and miRNAs) have a limited taxonomic range and provide a limited number of annotations. Recent improvements to the website, methodologies and data used by Rfam are discussed. Rfam is freely available on the Web at http://rfam.sanger.ac.uk/and http://rfam.janelia.org/.
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Affiliation(s)
- Paul P Gardner
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA, UK.
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Review of the selected proceedings of the Fifth International Workshop on Data Integration in the Life Sciences 2008. BMC Bioinformatics 2008; 9 Suppl 8:S1. [PMID: 18673525 PMCID: PMC2500092 DOI: 10.1186/1471-2105-9-s8-s1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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