Measuring and modeling diffuse scattering in protein X-ray crystallography
Abstract
X-ray diffraction has the potential to provide rich information about the structural dynamics of macromolecules. To realize this potential, both Bragg scattering, which is currently used to derive macromolecular structures, and diffuse scattering, which reports on correlations in charge density variations, must be measured. Until now, measurement of diffuse scattering from protein crystals has been scarce because of the extra effort of collecting diffuse data. Here, we present 3D measurements of diffuse intensity collected from crystals of the enzymes cyclophilin A and trypsin. The measurements were obtained from the same X-ray diffraction images as the Bragg data, using best practices for standard data collection. To model the underlying dynamics in a practical way that could be used during structure refinement, we tested translation-libration-screw (TLS), liquidlike motions (LLM), and coarse-grained normal-modes (NM) models of protein motions. The LLM model provides a global picture of motions and was refined against the diffuse data, whereas the TLS and NM models provide more detailed and distinct descriptions of atom displacements, and only used information from the Bragg data. Whereas different TLS groupings yielded similar Bragg intensities, they yielded different diffuse intensities, none of which agreed well with the data. In contrast, both the LLMmore »
- Authors:
-
[1];
- Univ. of California, San Francisco, CA (United States)
- SLAC National Accelerator Lab., Menlo Park, CA (United States). Stanford Synchrotron Radiation Lightsource (SSRL)
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Publication Date:
- Research Org.:
- SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES); USDOE Laboratory Directed Research and Development (LDRD) Program
- OSTI Identifier:
- 1257338
- Alternate Identifier(s):
- OSTI ID: 1321770; OSTI ID: 1379283
- Report Number(s):
- LA-UR-15-28934
Journal ID: ISSN 0027-8424
- Grant/Contract Number:
- AC02-76SF00515; GM095887; OD009180; GM110580; STC-1231306; MR-15-338599; AC52-06NA25396; AC02-05CH11231
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Proceedings of the National Academy of Sciences of the United States of America
- Additional Journal Information:
- Journal Volume: 113; Journal Issue: 15; Journal ID: ISSN 0027-8424
- Publisher:
- National Academy of Sciences, Washington, DC (United States)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; protein dynamics; normal modes; structural biology; diffuse scattering; liquid-like motions; 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; biological science
Citation Formats
Van Benschoten, Andrew H., Liu, Lin, Gonzalez, Ana, Brewster, Aaron S., Sauter, Nicholas K., Fraser, James S., and Wall, Michael E. Measuring and modeling diffuse scattering in protein X-ray crystallography. United States: N. p., 2016.
Web. doi:10.1073/pnas.1524048113.
Van Benschoten, Andrew H., Liu, Lin, Gonzalez, Ana, Brewster, Aaron S., Sauter, Nicholas K., Fraser, James S., & Wall, Michael E. Measuring and modeling diffuse scattering in protein X-ray crystallography. United States. https://doi.org/10.1073/pnas.1524048113
Van Benschoten, Andrew H., Liu, Lin, Gonzalez, Ana, Brewster, Aaron S., Sauter, Nicholas K., Fraser, James S., and Wall, Michael E. Mon .
"Measuring and modeling diffuse scattering in protein X-ray crystallography". United States. https://doi.org/10.1073/pnas.1524048113. https://www.osti.gov/servlets/purl/1257338.
@article{osti_1257338,
title = {Measuring and modeling diffuse scattering in protein X-ray crystallography},
author = {Van Benschoten, Andrew H. and Liu, Lin and Gonzalez, Ana and Brewster, Aaron S. and Sauter, Nicholas K. and Fraser, James S. and Wall, Michael E.},
abstractNote = {X-ray diffraction has the potential to provide rich information about the structural dynamics of macromolecules. To realize this potential, both Bragg scattering, which is currently used to derive macromolecular structures, and diffuse scattering, which reports on correlations in charge density variations, must be measured. Until now, measurement of diffuse scattering from protein crystals has been scarce because of the extra effort of collecting diffuse data. Here, we present 3D measurements of diffuse intensity collected from crystals of the enzymes cyclophilin A and trypsin. The measurements were obtained from the same X-ray diffraction images as the Bragg data, using best practices for standard data collection. To model the underlying dynamics in a practical way that could be used during structure refinement, we tested translation-libration-screw (TLS), liquidlike motions (LLM), and coarse-grained normal-modes (NM) models of protein motions. The LLM model provides a global picture of motions and was refined against the diffuse data, whereas the TLS and NM models provide more detailed and distinct descriptions of atom displacements, and only used information from the Bragg data. Whereas different TLS groupings yielded similar Bragg intensities, they yielded different diffuse intensities, none of which agreed well with the data. In contrast, both the LLM and NM models agreed substantially with the diffuse data. These results demonstrate a realistic path to increase the number of diffuse datasets available to the wider biosciences community and indicate that dynamics-inspired NM structural models can simultaneously agree with both Bragg and diffuse scattering.},
doi = {10.1073/pnas.1524048113},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
number = 15,
volume = 113,
place = {United States},
year = {Mon Mar 28 00:00:00 EDT 2016},
month = {Mon Mar 28 00:00:00 EDT 2016}
}
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