uu.seUppsala University Publications
Change search
Link to record
Permanent link

Direct link
BETA
Kleywegt, Gerard J.
Alternative names
Publications (8 of 8) Show all publications
Read, R. J., Adams, P. D., Arendall, W. B., Brunger, A. T., Emsley, P., Joosten, R. P., . . . Zwart, P. H. (2011). A New Generation of Crystallographic Validation Tools for the Protein Data Bank. Structure, 19(10), 1395-1412
Open this publication in new window or tab >>A New Generation of Crystallographic Validation Tools for the Protein Data Bank
Show others...
2011 (English)In: Structure, ISSN 0969-2126, E-ISSN 1878-4186, Vol. 19, no 10, p. 1395-1412Article in journal (Refereed) Published
Abstract [en]

This report presents the conclusions of the X-ray Validation Task Force of the worldwide Protein Data Bank (PDB). The PDB has expanded massively since current criteria for validation of deposited structures were adopted, allowing a much more sophisticated understanding of all the components of macromolecular crystals. The size of the PDB creates new opportunities to validate structures by comparison with the existing database, and the now-mandatory deposition of structure factors creates new opportunities to validate the underlying diffraction data. These developments highlighted the need for a now assessment of validation criteria. The Task Force recommends that a small set of validation data be presented in an easily understood format, relative to both the full PDB and the applicable resolution class, with greater detail available to interested users. Most importantly, we recommend that referees and editors judging the quality of structural experiments have access to a concise summary of well-established quality indicators.

National Category
Natural Sciences
Identifiers
urn:nbn:se:uu:diva-161463 (URN)10.1016/j.str.2011.08.006 (DOI)000296125100009 ()
Available from: 2011-11-14 Created: 2011-11-14 Last updated: 2017-12-08Bibliographically approved
Gorbalenya, A. E., Lieutaud, P., Harris, M. R., Coutard, B., Canard, B., Kleywegt, G. J., . . . Jones, T. A. (2010). Practical application of bioinformatics by the multidisciplinary VIZIER consortium. Antiviral Research, 87(2), 95-110
Open this publication in new window or tab >>Practical application of bioinformatics by the multidisciplinary VIZIER consortium
Show others...
2010 (English)In: Antiviral Research, ISSN 0166-3542, E-ISSN 1872-9096, Vol. 87, no 2, p. 95-110Article, review/survey (Refereed) Published
Abstract [en]

This review focuses on bioinformatics technologies employed by the EU-sponsored multidisciplinary VIZIER consortium (Comparative Structural Genomics of Viral Enzymes Involved in Replication, FP6 Project: 2004-511960, active from 1 November 2004 to 30 April 2009), to achieve its goals. From the management of the information flow of the project, to bioinformatics-mediated selection of RNA viruses and prediction of protein targets, to the analysis of 3D protein structures and antiviral compounds, these technologies provided a communication framework and integrated solutions for steady and timely advancement of the project. RNA viruses form a large class of major pathogens that affect humans and domestic animals. Such RNA viruses as HIV, Influenza virus and Hepatitis C virus are of prime medical concern today, but the identities of viruses that will threaten human population tomorrow are far from certain. To contain outbreaks of common or newly emerging infections, prototype drugs against viruses representing the Virus Universe must be developed. This concept was championed by the VIZIER project which brought together experts in diverse fields to produce a concerted and sustained effort for identifying and validating targets for antivirus therapy in dozens of RNA virus lineages.

Place, publisher, year, edition, pages
Elsevier, 2010
Keywords
VIZIER, VaZyMolO, VirAliS, Xtrack, EDBase
National Category
Structural Biology
Identifiers
urn:nbn:se:uu:diva-130679 (URN)10.1016/j.antiviral.2010.02.005 (DOI)000280972700002 ()20153379 (PubMedID)
Available from: 2010-09-10 Created: 2010-09-10 Last updated: 2017-12-12Bibliographically approved
Strömbergsson, H., Lapins, M., Kleywegt, G. J. & Wikberg, J. E. S. (2010). Towards proteome-wide interaction models using the proteochemometrics approach. Molecular Informatics, 29(6-7), 499-508
Open this publication in new window or tab >>Towards proteome-wide interaction models using the proteochemometrics approach
2010 (English)In: Molecular Informatics, ISSN 1868-1743, Vol. 29, no 6-7, p. 499-508Article in journal (Refereed) Published
Abstract [en]

A proteochemometrics model was induced from all interaction data in the BindingDB database, comprizing in all 7078 protein-ligand complexes with representatives from all major drug target categories. Proteins were represented by alignment-independent sequence descriptors holding information on properties such as hydrophobicity, charge, and secondary structure. Ligands were represented by commonly used QSAR descriptors. The inhibition constant (pK(i)) values of protein-ligand complexes were discretized into "high" and "low" interaction activity. Different machine-learning techniques were used to induce models relating protein and ligand properties to the interaction activity. The best was decision trees, which gave an accuracy of 80% and an area under the ROC curve of 0.81. The tree pointed to the protein and ligand properties, which are relevant for the interaction. As the approach does neither require alignments nor knowledge of protein 3D structures virtually all available protein-ligand interaction data could be utilized, thus opening a way to completely general interaction models that may span entire proteomes.

Keywords
Bioinformatics, Chemogenomics, Drug design, Protein-Ligand interactions, Proteochemometrics
National Category
Pharmaceutical Sciences Biological Sciences
Identifiers
urn:nbn:se:uu:diva-89298 (URN)10.1002/minf.201000052 (DOI)000280908200004 ()
Available from: 2009-02-10 Created: 2009-02-10 Last updated: 2018-01-13Bibliographically approved
Novotny, M., Seibert, M. & Kleywegt, G. (2007). On the precision of calculated solvent-accessible surface areas. Acta Crystallographica Section D: Biological Crystallography, 63(2), 270-274
Open this publication in new window or tab >>On the precision of calculated solvent-accessible surface areas
2007 (English)In: Acta Crystallographica Section D: Biological Crystallography, ISSN 0907-4449, E-ISSN 1399-0047, Vol. 63, no 2, p. 270-274Article in journal (Refereed) Published
Abstract [en]

The fact that protein structures are dynamic by nature and that structure models determined by X-ray crystallography, electron microscopy (EM) and nuclear magnetic resonance (NMR) spectroscopy have limited accuracy limits the precision with which derived properties can be reported. Here, the issue of the precision of calculated solvent-accessible surface areas (ASAs) is addressed. A number of protein structures of different sizes were selected and the effect of random shifts applied to the atomic coordinates on ASA values was investigated. Standard deviations of the ASA calculations were found to range from ∼10 to ∼80  Å2. Similar values are obtained for a handful of cases in the Protein Data Bank (PDB) where `ensembles' of crystal structures were refined against the same data set. The ASA values for 69 hen egg-white lysozyme structures were calculated and a standard deviation of the ASA of 81  Å2 was obtained (the average ASA value was 6571  Å2). The calculated ASA values do not show any correlation with factors such as resolution or overall temperature factors. A molecular-dynamics (MD) trajectory of lysozyme was also analysed. The ASA values during the simulation covered a range of more than 800  Å2. If different programs are used, the ASA values obtained for one small protein show a spread of almost 600  Å2. These results suggest that in most cases reporting ASA values with a precision better than 10  Å2 is probably not realistic and a precision of 50–100  Å2 would seem prudent. The precision of buried surface-area calculations for complexes is also discussed.

Keywords
precision, solvent-accessible surface-area calculations, molecular dynamics
National Category
Biological Sciences
Identifiers
urn:nbn:se:uu:diva-95502 (URN)10.1107/S0907444906044118 (DOI)000243495700017 ()17242521 (PubMedID)
Available from: 2007-03-01 Created: 2007-03-01 Last updated: 2017-12-14Bibliographically approved
Kleywegt, G. J. (2007). Separating model optimization and model validation in statistical cross-validation as applied to crystallography.. Acta Crystallographica Section D: Biological Crystallography, 63(9), 939-940
Open this publication in new window or tab >>Separating model optimization and model validation in statistical cross-validation as applied to crystallography.
2007 (English)In: Acta Crystallographica Section D: Biological Crystallography, ISSN 0907-4449, E-ISSN 1399-0047, Vol. 63, no 9, p. 939-940Article in journal (Refereed) Published
Abstract [en]

Statistical cross-validation has become an integral part of the model-refinement process in macromolecular crystallography. However, the test set of reflections, for which the free R value is calculated, is used both to optimize the parameterization of the structure model and to validate the model itself. This practice could introduce bias and diminish the value of R(free) as an independent check of model quality. It is proposed here that by introducing a dormant hold-out set of reflections, any problems with such bias can be avoided. This procedure requires only a small modification of the standard cross-validation protocol.

Keywords
cross-validation, model optimization, model validation.
National Category
Biological Sciences
Identifiers
urn:nbn:se:uu:diva-13665 (URN)10.1107/S0907444907033458 (DOI)17704561 (PubMedID)
Available from: 2008-06-05 Created: 2008-06-05 Last updated: 2017-12-11Bibliographically approved
Kleywegt, G. J. & Harris, M. R. (2007). ValLigURL: a server for ligand-structure comparison and validation. Acta Crystallographica Section D: Biological Crystallography, 63, 935-938
Open this publication in new window or tab >>ValLigURL: a server for ligand-structure comparison and validation
2007 (English)In: Acta Crystallographica Section D: Biological Crystallography, ISSN 0907-4449, E-ISSN 1399-0047, Vol. 63, p. 935-938Article in journal (Refereed) Published
Abstract [en]

A new web-based tool called ValLigURL is described. It can be used by practising crystallographers to validate the geometry of a ligand and to compare the conformation of a ligand with all instances of that ligand in the structural database (wwPDB). In addition, it can be used by structural bioinformaticians to survey the quality or conformational diversity of any ligand across the entire structural database. The server is freely accessible at the URL http://eds.bmc.uu.se/eds/valligurl.php.

Keywords
Computational Biology/*methods, Databases; Factual, Internet, Ligands, Models; Molecular, Molecular Conformation, Mycobacterium tuberculosis/chemistry, NADP/chemistry, Reproducibility of Results
National Category
Biological Sciences
Identifiers
urn:nbn:se:uu:diva-13666 (URN)10.1107/S090744490703315X (DOI)000248078400011 ()17642521 (PubMedID)
Available from: 2008-06-05 Created: 2008-06-05 Last updated: 2017-12-11Bibliographically approved
Kleywegt, G. J., Harris, M. R., Zou, J. Y., Taylor, T. C., Wählby, A. & Jones, T. A. (2004). The Uppsala Electron-Density Server. Acta Crystallographica Section D: Biological Crystallography, 60(Pt 12 Pt 1), 2240-2249
Open this publication in new window or tab >>The Uppsala Electron-Density Server
Show others...
2004 (English)In: Acta Crystallographica Section D: Biological Crystallography, ISSN 0907-4449, E-ISSN 1399-0047, Vol. 60, no Pt 12 Pt 1, p. 2240-2249Article in journal (Refereed) Published
Abstract [en]

The Uppsala Electron Density Server (EDS; http://eds.bmc.uu.se/) is a web-based facility that provides access to electron-density maps and statistics concerning the fit of crystal structures and their maps. Maps are available for approximately 87% of the crystallographic Protein Data Bank (PDB) entries for which structure factors have been deposited and for which straightforward map calculations succeed in reproducing the published R value to within five percentage points. Here, an account is provided of the methods that are used to generate the information contained in the server. Some of the problems that are encountered in the map-generation process as well as some spin-offs of the project are also discussed.

Keywords
Computational Biology, Crystallography; X-Ray, Databases; Protein, Electrons, Internet, Proteins/chemistry, Reproducibility of Results, Research Support; Non-U.S. Gov't, Software, Temperature
National Category
Natural Sciences
Identifiers
urn:nbn:se:uu:diva-71671 (URN)15572777 (PubMedID)
Available from: 2006-12-15 Created: 2006-12-15 Last updated: 2017-11-21Bibliographically approved
Jones, T. A., Kleywegt, G. J. & Brunger, A. T. (1996). Storing diffraction data.. Nature, 383(6595), 18-9
Open this publication in new window or tab >>Storing diffraction data.
1996 (English)In: Nature, ISSN 0028-0836, Vol. 383, no 6595, p. 18-9Article in journal (Other (popular scientific, debate etc.)) Published
Keywords
Crystallography; X-Ray, Databases; Factual, Protein Conformation, Publishing, Quality Control
Identifiers
urn:nbn:se:uu:diva-13670 (URN)8779705 (PubMedID)
Available from: 2008-01-24 Created: 2008-01-24 Last updated: 2011-01-15
Organisations

Search in DiVA

Show all publications