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Solving protein structure from sparse serial microcrystal diffraction data at a storage-ring synchrotron source
In recent years, the success of serial femtosecond crystallography and the paucity of beamtime at X-ray free-electron lasers have motivated the development of serial microcrystallography experiments at storage-ring synchrotron sources. However, especially at storage-ring sources, if a crystal is too...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Union of Crystallography
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6126656/ https://www.ncbi.nlm.nih.gov/pubmed/30224958 http://dx.doi.org/10.1107/S205225251800903X |
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author | Lan, Ti-Yen Wierman, Jennifer L. Tate, Mark W. Philipp, Hugh T. Martin-Garcia, Jose M. Zhu, Lan Kissick, David Fromme, Petra Fischetti, Robert F. Liu, Wei Elser, Veit Gruner, Sol M. |
author_facet | Lan, Ti-Yen Wierman, Jennifer L. Tate, Mark W. Philipp, Hugh T. Martin-Garcia, Jose M. Zhu, Lan Kissick, David Fromme, Petra Fischetti, Robert F. Liu, Wei Elser, Veit Gruner, Sol M. |
author_sort | Lan, Ti-Yen |
collection | PubMed |
description | In recent years, the success of serial femtosecond crystallography and the paucity of beamtime at X-ray free-electron lasers have motivated the development of serial microcrystallography experiments at storage-ring synchrotron sources. However, especially at storage-ring sources, if a crystal is too small it will have suffered significant radiation damage before diffracting a sufficient number of X-rays into Bragg peaks for peak-indexing software to determine the crystal orientation. As a consequence, the data frames of small crystals often cannot be indexed and are discarded. Introduced here is a method based on the expand–maximize–compress (EMC) algorithm to solve protein structures, specifically from data frames for which indexing methods fail because too few X-rays are diffracted into Bragg peaks. The method is demonstrated on a real serial microcrystallography data set whose signals are too weak to be indexed by conventional methods. In spite of the daunting background scatter from the sample-delivery medium, it was still possible to solve the protein structure at 2.1 Å resolution. The ability of the EMC algorithm to analyze weak data frames will help to reduce sample consumption. It will also allow serial microcrystallography to be performed with crystals that are otherwise too small to be feasibly analyzed at storage-ring sources. |
format | Online Article Text |
id | pubmed-6126656 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | International Union of Crystallography |
record_format | MEDLINE/PubMed |
spelling | pubmed-61266562018-09-17 Solving protein structure from sparse serial microcrystal diffraction data at a storage-ring synchrotron source Lan, Ti-Yen Wierman, Jennifer L. Tate, Mark W. Philipp, Hugh T. Martin-Garcia, Jose M. Zhu, Lan Kissick, David Fromme, Petra Fischetti, Robert F. Liu, Wei Elser, Veit Gruner, Sol M. IUCrJ Research Papers In recent years, the success of serial femtosecond crystallography and the paucity of beamtime at X-ray free-electron lasers have motivated the development of serial microcrystallography experiments at storage-ring synchrotron sources. However, especially at storage-ring sources, if a crystal is too small it will have suffered significant radiation damage before diffracting a sufficient number of X-rays into Bragg peaks for peak-indexing software to determine the crystal orientation. As a consequence, the data frames of small crystals often cannot be indexed and are discarded. Introduced here is a method based on the expand–maximize–compress (EMC) algorithm to solve protein structures, specifically from data frames for which indexing methods fail because too few X-rays are diffracted into Bragg peaks. The method is demonstrated on a real serial microcrystallography data set whose signals are too weak to be indexed by conventional methods. In spite of the daunting background scatter from the sample-delivery medium, it was still possible to solve the protein structure at 2.1 Å resolution. The ability of the EMC algorithm to analyze weak data frames will help to reduce sample consumption. It will also allow serial microcrystallography to be performed with crystals that are otherwise too small to be feasibly analyzed at storage-ring sources. International Union of Crystallography 2018-07-20 /pmc/articles/PMC6126656/ /pubmed/30224958 http://dx.doi.org/10.1107/S205225251800903X Text en © Ti-Yen Lan et al. 2018 http://creativecommons.org/licenses/by/2.0/uk/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.http://creativecommons.org/licenses/by/2.0/uk/ |
spellingShingle | Research Papers Lan, Ti-Yen Wierman, Jennifer L. Tate, Mark W. Philipp, Hugh T. Martin-Garcia, Jose M. Zhu, Lan Kissick, David Fromme, Petra Fischetti, Robert F. Liu, Wei Elser, Veit Gruner, Sol M. Solving protein structure from sparse serial microcrystal diffraction data at a storage-ring synchrotron source |
title | Solving protein structure from sparse serial microcrystal diffraction data at a storage-ring synchrotron source |
title_full | Solving protein structure from sparse serial microcrystal diffraction data at a storage-ring synchrotron source |
title_fullStr | Solving protein structure from sparse serial microcrystal diffraction data at a storage-ring synchrotron source |
title_full_unstemmed | Solving protein structure from sparse serial microcrystal diffraction data at a storage-ring synchrotron source |
title_short | Solving protein structure from sparse serial microcrystal diffraction data at a storage-ring synchrotron source |
title_sort | solving protein structure from sparse serial microcrystal diffraction data at a storage-ring synchrotron source |
topic | Research Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6126656/ https://www.ncbi.nlm.nih.gov/pubmed/30224958 http://dx.doi.org/10.1107/S205225251800903X |
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