Rapid interpretation of small-angle X-ray scattering data.
The fundamental aim of structural analyses in biophysics is to reveal a mutual relation between a molecule's dynamic structure and its physiological function. Small-angle X-ray scattering (SAXS) is an experimental technique for structural characterization of macromolecules in solution and enabl...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2019-03-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1006900 |
| _version_ | 1819020313895108608 |
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| author | Marie Weiel Ines Reinartz Alexander Schug |
| author_facet | Marie Weiel Ines Reinartz Alexander Schug |
| author_sort | Marie Weiel |
| collection | DOAJ |
| description | The fundamental aim of structural analyses in biophysics is to reveal a mutual relation between a molecule's dynamic structure and its physiological function. Small-angle X-ray scattering (SAXS) is an experimental technique for structural characterization of macromolecules in solution and enables time-resolved analysis of conformational changes under physiological conditions. As such experiments measure spatially averaged low-resolution scattering intensities only, the sparse information obtained is not sufficient to uniquely reconstruct a three-dimensional atomistic model. Here, we integrate the information from SAXS into molecular dynamics simulations using computationally efficient native structure-based models. Dynamically fitting an initial structure towards a scattering intensity, such simulations produce atomistic models in agreement with the target data. In this way, SAXS data can be rapidly interpreted while retaining physico-chemical knowledge and sampling power of the underlying force field. We demonstrate our method's performance using the example of three protein systems. Simulations are faster than full molecular dynamics approaches by more than two orders of magnitude and consistently achieve comparable accuracy. Computational demands are reduced sufficiently to run the simulations on commodity desktop computers instead of high-performance computing systems. These results underline that scattering-guided structure-based simulations provide a suitable framework for rapid early-stage refinement of structures towards SAXS data with particular focus on minimal computational resources and time. |
| first_indexed | 2024-12-21T03:49:14Z |
| format | Article |
| id | doaj.art-3446b919f31949fd83e5622c78299ba4 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-21T03:49:14Z |
| publishDate | 2019-03-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-3446b919f31949fd83e5622c78299ba42022-12-21T19:17:01ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582019-03-01153e100690010.1371/journal.pcbi.1006900Rapid interpretation of small-angle X-ray scattering data.Marie WeielInes ReinartzAlexander SchugThe fundamental aim of structural analyses in biophysics is to reveal a mutual relation between a molecule's dynamic structure and its physiological function. Small-angle X-ray scattering (SAXS) is an experimental technique for structural characterization of macromolecules in solution and enables time-resolved analysis of conformational changes under physiological conditions. As such experiments measure spatially averaged low-resolution scattering intensities only, the sparse information obtained is not sufficient to uniquely reconstruct a three-dimensional atomistic model. Here, we integrate the information from SAXS into molecular dynamics simulations using computationally efficient native structure-based models. Dynamically fitting an initial structure towards a scattering intensity, such simulations produce atomistic models in agreement with the target data. In this way, SAXS data can be rapidly interpreted while retaining physico-chemical knowledge and sampling power of the underlying force field. We demonstrate our method's performance using the example of three protein systems. Simulations are faster than full molecular dynamics approaches by more than two orders of magnitude and consistently achieve comparable accuracy. Computational demands are reduced sufficiently to run the simulations on commodity desktop computers instead of high-performance computing systems. These results underline that scattering-guided structure-based simulations provide a suitable framework for rapid early-stage refinement of structures towards SAXS data with particular focus on minimal computational resources and time.https://doi.org/10.1371/journal.pcbi.1006900 |
| spellingShingle | Marie Weiel Ines Reinartz Alexander Schug Rapid interpretation of small-angle X-ray scattering data. PLoS Computational Biology |
| title | Rapid interpretation of small-angle X-ray scattering data. |
| title_full | Rapid interpretation of small-angle X-ray scattering data. |
| title_fullStr | Rapid interpretation of small-angle X-ray scattering data. |
| title_full_unstemmed | Rapid interpretation of small-angle X-ray scattering data. |
| title_short | Rapid interpretation of small-angle X-ray scattering data. |
| title_sort | rapid interpretation of small angle x ray scattering data |
| url | https://doi.org/10.1371/journal.pcbi.1006900 |
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