For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
76
views
39
references
 Top references
cited by
190
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      407
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: not found

      Robust, high-throughput solution structural analyses by small angle X-ray scattering (SAXS)

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          We present an efficient pipeline enabling high-throughput analysis of protein structure in solution with small angle X-ray scattering (SAXS). Our SAXS pipeline combines automated sample handling of microliter volumes, temperature and anaerobic control, rapid data collection, data analysis, and couples structural analysis with automated archiving. We subjected 50 representative proteins, mostly from Pyrococcus furiosus, to this pipeline, revealing that 30 were multimeric structures in solution. SAXS analysis allowed us to distinguish aggregated and unfolded proteins, define global structural parameters and oligomeric states for most samples, identify shapes and similar structures for 25 unknown structures, and determine envelopes for 41 proteins. We believe that high throughput SAXS is an enabling technology that may change the way that structural genomics research is done.

          Related collections

          Most cited references39

          • Record: found
          • Abstract: found
          • Article: not found

          PROSITE: a documented database using patterns and profiles as motif descriptors.

          Christian J A Sigrist, Lorenzo Cerutti, Nicolas Hulo … (2002)
          Among the various databases dedicated to the identification of protein families and domains, PROSITE is the first one created and has continuously evolved since. PROSITE currently consists of a large collection of biologically meaningful motifs that are described as patterns or profiles, and linked to documentation briefly describing the protein family or domain they are designed to detect. The close relationship of PROSITE with the SWISS-PROT protein database allows the evaluation of the sensitivity and specificity of the PROSITE motifs and their periodic reviewing. In return, PROSITE is used to help annotate SWISS-PROT entries. The main characteristics and the techniques of family and domain identification used by PROSITE are reviewed in this paper.
          Article 0 comments Cited 242 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Global rigid body modeling of macromolecular complexes against small-angle scattering data.

            Maxim Petoukhov, Dmitri I. Svergun (2005)
            New methods to automatically build models of macromolecular complexes from high-resolution structures or homology models of their subunits or domains against x-ray or neutron small-angle scattering data are presented. Depending on the complexity of the object, different approaches are employed for the global search of the optimum configuration of subunits fitting the experimental data. An exhaustive grid search is used for hetero- and homodimeric particles and for symmetric oligomers formed by identical subunits. For the assemblies or multidomain proteins containing more then one subunit/domain per asymmetric unit, heuristic algorithms based on simulated annealing are used. Fast computational algorithms based on spherical harmonics representation of scattering amplitudes are employed. The methods allow one to construct interconnected models without steric clashes, to account for the particle symmetry and to incorporate information from other methods, on distances between specific residues or nucleotides. For multidomain proteins, addition of missing linkers between the domains is possible. Simultaneous fitting of multiple scattering patterns from subcomplexes or deletion mutants is incorporated. The efficiency of the methods is illustrated by their application to complexes of different types in several simulated and practical examples. Limitations and possible ambiguity of rigid body modeling are discussed and simplified docking criteria are provided to rank multiple models. The methods described are implemented in publicly available computer programs running on major hardware platforms.
            Article 0 comments Cited 235 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The molecular sociology of the cell.

              V Robinson, Wolfgang Baumeister, Andrej Sali (2007)
              Proteomic studies have yielded detailed lists of the proteins present in a cell. Comparatively little is known, however, about how these proteins interact and are spatially arranged within the 'functional modules' of the cell: that is, the 'molecular sociology' of the cell. This gap is now being bridged by using emerging experimental techniques, such as mass spectrometry of complexes and single-particle cryo-electron microscopy, to complement traditional biochemical and biophysical methods. With the development of integrative computational methods to exploit the data obtained, such hybrid approaches will uncover the molecular architectures, and perhaps even atomic models, of many protein complexes. With these structures in hand, researchers will be poised to use cryo-electron tomography to view protein complexes in action within cells, providing unprecedented insights into protein-interaction networks.
              Article 0 comments Cited 109 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Journal
                Journal ID (nlm-journal-id): 101215604
                Journal ID (pubmed-jr-id): 32338
                Journal ID (nlm-ta): Nat Methods
                Journal ID (iso-abbrev): Nat. Methods
                Title: Nature methods
                ISSN (Print): 1548-7091
                ISSN (Electronic): 1548-7105
                Publication date Nihms-submitted: 6 May 2011
                Publication date (Electronic): 20 July 2009
                Publication date (Print): August 2009
                Publication date PMC-release: 14 May 2011
                Volume: 6
                Issue: 8
                Pages: 606-612
                Affiliations
                [1 ]Physical Bioscience Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720
                [2 ]Life Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720
                [3 ]Georgia Campus Philadelphia College of Osteopathic Medicine, Suwanee, GA 30024
                [4 ]Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602
                [5 ]Department of Molecular Biology and The Skaggs Institute for Chemical Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037
                Author notes
                [* ]Corresponding authors- jat@ 123456scripps.edu
                [†]

                Contributed equally to this work

                Article
                Manuscript ID: nihpa293392
                DOI: 10.1038/nmeth.1353
                PMC ID: 3094553
                PubMed ID: 19620974
                SO-VID: 64150302-1837-4de3-99c8-77c4d6aefe81
                License:

                Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

                History
                Funding
                Funded by: National Cancer Institute : NCI
                Award ID: R01 CA117638-08 || CA
                Funded by: National Cancer Institute : NCI
                Award ID: R01 CA117638-07 || CA
                Funded by: National Cancer Institute : NCI
                Award ID: R01 CA117638-06 || CA
                Categories
                Subject: Article

                ScienceOpen disciplines: Life sciences
                Data availability:
                ScienceOpen disciplines: Life sciences

                Comments

                Comment on this article

                scite_

                Similar content407

                See all similar

                Cited by182

                See all cited by

                Most referenced authors1,386

                See all reference authors