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Joosten RP, Salzemann J, Bloch V, Stockinger H, Berglund AC, Blanchet C, Bongcam-Rudloff E, Combet C, Da Costa AL, Deleage G, Diarena M, Fabbretti R, Fettahi G, Flegel V, Gisel A, Kasam V, Kervinen T, Korpelainen E, Mattila K, Pagni M, Reichstadt M, Breton V, Tickle IJ, Vriend G. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr 2009; 42:376-384. [PMID: 22477769 PMCID: PMC3246819 DOI: 10.1107/s0021889809008784] [Citation(s) in RCA: 169] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2009] [Accepted: 03/10/2009] [Indexed: 11/24/2022] Open
Abstract
Structural biology, homology modelling and rational drug design require accurate three-dimensional macromolecular coordinates. However, the coordinates in the Protein Data Bank (PDB) have not all been obtained using the latest experimental and computational methods. In this study a method is presented for automated re-refinement of existing structure models in the PDB. A large-scale benchmark with 16 807 PDB entries showed that they can be improved in terms of fit to the deposited experimental X-ray data as well as in terms of geometric quality. The re-refinement protocol uses TLS models to describe concerted atom movement. The resulting structure models are made available through the PDB_REDO databank (http://www.cmbi.ru.nl/pdb_redo/). Grid computing techniques were used to overcome the computational requirements of this endeavour.
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Affiliation(s)
- Robbie P. Joosten
- Centre for Molecular and Biomolecular Informatics, NCMLS, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jean Salzemann
- CNRS/IN2P3, Laboratoire de Physique Corpusculaire, Université Blaize Pascal, Clermont-Ferrand, France
| | - Vincent Bloch
- CNRS/IN2P3, Laboratoire de Physique Corpusculaire, Université Blaize Pascal, Clermont-Ferrand, France
| | - Heinz Stockinger
- Swiss Institute of Bioinformatics, Vital-IT Group, Lausanne, Switzerland
| | | | - Christophe Blanchet
- IBCP, CNRS Université de Lyon1, IFR128 BioSciences Lyon-Gerland, Lyon, France
| | | | - Christophe Combet
- IBCP, CNRS Université de Lyon1, IFR128 BioSciences Lyon-Gerland, Lyon, France
| | - Ana L. Da Costa
- CNRS/IN2P3, Laboratoire de Physique Corpusculaire, Université Blaize Pascal, Clermont-Ferrand, France
| | - Gilbert Deleage
- IBCP, CNRS Université de Lyon1, IFR128 BioSciences Lyon-Gerland, Lyon, France
| | - Matteo Diarena
- CNRS/IN2P3, Laboratoire de Physique Corpusculaire, Université Blaize Pascal, Clermont-Ferrand, France
| | - Roberto Fabbretti
- Swiss Institute of Bioinformatics, Vital-IT Group, Lausanne, Switzerland
| | - Géraldine Fettahi
- CNRS/IN2P3, Laboratoire de Physique Corpusculaire, Université Blaize Pascal, Clermont-Ferrand, France
| | - Volker Flegel
- Swiss Institute of Bioinformatics, Vital-IT Group, Lausanne, Switzerland
| | - Andreas Gisel
- Institute for Biomedical Technologies Bari, CNR, Bari, Italy
| | - Vinod Kasam
- Fraunhofer-Institute for Algorithms and Scientific Computing, Sankt Augustin, Germany
| | - Timo Kervinen
- CSC – The Finnish IT Center for Science, Espoo, Finland
| | | | - Kimmo Mattila
- CSC – The Finnish IT Center for Science, Espoo, Finland
| | - Marco Pagni
- Swiss Institute of Bioinformatics, Vital-IT Group, Lausanne, Switzerland
| | - Matthieu Reichstadt
- CNRS/IN2P3, Laboratoire de Physique Corpusculaire, Université Blaize Pascal, Clermont-Ferrand, France
| | - Vincent Breton
- CNRS/IN2P3, Laboratoire de Physique Corpusculaire, Université Blaize Pascal, Clermont-Ferrand, France
| | | | - Gert Vriend
- Centre for Molecular and Biomolecular Informatics, NCMLS, Radboud University Medical Center, Nijmegen, The Netherlands
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Binz PA, Müller M, Walther D, Bienvenut WV, Gras R, Hoogland C, Bouchet G, Gasteiger E, Fabbretti R, Gay S, Palagi P, Wilkins MR, Rouge V, Tonella L, Paesano S, Rossellat G, Karmime A, Bairoch A, Sanchez JC, Appel RD, Hochstrasser DF. A molecular scanner to automate proteomic research and to display proteome images. Anal Chem 1999; 71:4981-8. [PMID: 10565287 DOI: 10.1021/ac990449e] [Citation(s) in RCA: 93] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Identification and characterization of all proteins expressed by a genome in biological samples represent major challenges in proteomics. Today's commonly used high-throughput approaches combine two-dimensional electrophoresis (2-DE) with peptide mass fingerprinting (PMF) analysis. Although automation is often possible, a number of limitations still adversely affect the rate of protein identification and annotation in 2-DE databases: the sequential excision process of pieces of gel containing protein; the enzymatic digestion step; the interpretation of mass spectra (reliability of identifications); and the manual updating of 2-DE databases. We present a highly automated method that generates a fully annoated 2-DE map. Using a parallel process, all proteins of a 2-DE are first simultaneously digested proteolytically and electro-transferred onto a poly(vinylidene difluoride) membrane. The membrane is then directly scanned by MALDI-TOF MS. After automated protein identification from the obtained peptide mass fingerprints using PeptIdent software (http://www.expasy.ch/tools/peptident.html + ++), a fully annotated 2-D map is created on-line. It is a multidimensional representation of a proteome that contains interpreted PMF data in addition to protein identification results. This "MS-imaging" method represents a major step toward the development of a clinical molecular scanner.
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Affiliation(s)
- P A Binz
- Swiss Institute of Bioinformatics, University Medical Center, Geneva, Switzerland.
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Fabbretti R, Dorsaz PA, Doriot PA, Rutishauser W. Applying the object paradigm to a centralized database for a cardiology division. Int J Biomed Comput 1996; 42:129-34. [PMID: 8880279 DOI: 10.1016/0020-7101(96)01191-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
In order to master the overwhelming quantity of data produced by the different laboratories of our Cardiology Division, we are presently developing a centralized database. Our aim is to improve the quality of diagnoses and therapies by constituting patient centered medical files integrating logically the results of the results of the different examinations and allowing for a rapid access to the patient data. The database has to be accessible from an heterogeneous set of PC, MacIntoshes and UNIX workstations. It must have an ergonomic graphic user interface and generate reports which can be sent to the patient physician. It is well known that the requirements for a medical database make its conceptual analysis very difficult. As medical knowledge continually evolves, the examination protocols change and, therefore, the data sets have to be updated. The maintenance of classical databases is usually expensive because it requires specialized staff to alter the database structure and to adapt the user interface. To allow for flexibility, modularity, code reusability and reliability, the object paradigm was applied to a classical relational database. Thanks to the combination of both data structure and behavior in single entities, it is possible to build generic user interfaces which can be easily tailored to the needs of every laboratory of our Cardiology Division.
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Affiliation(s)
- R Fabbretti
- Cardiology Division, University Hospital of Geneva, Switzerland
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