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      FoXS: a web server for rapid computation and fitting of SAXS profiles

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          Abstract

          Small angle X-ray scattering (SAXS) is an increasingly common technique for low-resolution structural characterization of molecules in solution. SAXS experiment determines the scattering intensity of a molecule as a function of spatial frequency, termed SAXS profile. SAXS profiles can contribute to many applications, such as comparing a conformation in solution with the corresponding X-ray structure, modeling a flexible or multi-modular protein, and assembling a macromolecular complex from its subunits. These applications require rapid computation of a SAXS profile from a molecular structure. FoXS (Fast X-Ray Scattering) is a rapid method for computing a SAXS profile of a given structure and for matching of the computed and experimental profiles. Here, we describe the interface and capabilities of the FoXS web server ( http://salilab.org/foxs).

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          Most cited references27

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          Determination of domain structure of proteins from X-ray solution scattering.

          An ab initio method for building structural models of proteins from x-ray solution scattering data is presented. Simulated annealing is employed to find a chain-compatible spatial distribution of dummy residues which fits the experimental scattering pattern up to a resolution of 0.5 nm. The efficiency of the method is illustrated by the ab initio reconstruction of models of several proteins, with known and unknown crystal structure, from experimental scattering data. The new method substantially improves the resolution and reliability of models derived from scattering data and makes solution scattering a useful technique in large-scale structural characterization of proteins.
            • Record: found
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            Global rigid body modeling of macromolecular complexes against small-angle scattering data.

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

              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.

                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                1 July 2010
                27 May 2010
                27 May 2010
                : 38
                : Web Server issue
                : W540-W544
                Affiliations
                1Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences (QB3), University of California at San Francisco, CA 94158 and 2Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
                Author notes
                *To whom correspondence should be addressed. Tel: +1 415 514 4227; Fax: +1 415 514 4231; Email: sali@ 123456salilab.org
                Article
                gkq461
                10.1093/nar/gkq461
                2896111
                20507903
                d99bbaaa-8be9-42ea-96f3-f1e22ec3e7e8
                Published by Oxford University Press (2010).

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 28 January 2010
                : 30 April 2010
                : 11 May 2010
                Categories
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                Genetics
                Genetics

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