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A simple technique to classify diffraction data from dynamic proteins according to individual polymorphs
One often observes small but measurable differences in the diffraction data measured from different crystals of a single protein. These differences might reflect structural differences in the protein and may reveal the natural dynamism of the molecule in solution. Partitioning these mixed-state data...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Union of Crystallography
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8900820/ https://www.ncbi.nlm.nih.gov/pubmed/35234141 http://dx.doi.org/10.1107/S2059798321013425 |
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author | Nguyen, Thu Phan, Kim L. Kozakov, Dima Gabelli, Sandra B. Kreitler, Dale F. Andrews, Lawrence C. Jakoncic, Jean Sweet, Robert M. Soares, Alexei S. Bernstein, Herbert J. |
author_facet | Nguyen, Thu Phan, Kim L. Kozakov, Dima Gabelli, Sandra B. Kreitler, Dale F. Andrews, Lawrence C. Jakoncic, Jean Sweet, Robert M. Soares, Alexei S. Bernstein, Herbert J. |
author_sort | Nguyen, Thu |
collection | PubMed |
description | One often observes small but measurable differences in the diffraction data measured from different crystals of a single protein. These differences might reflect structural differences in the protein and may reveal the natural dynamism of the molecule in solution. Partitioning these mixed-state data into single-state clusters is a critical step that could extract information about the dynamic behavior of proteins from hundreds or thousands of single-crystal data sets. Mixed-state data can be obtained deliberately (through intentional perturbation) or inadvertently (while attempting to measure highly redundant single-crystal data). To the extent that different states adopt different molecular structures, one expects to observe differences in the crystals; each of the polystates will create a polymorph of the crystals. After mixed-state diffraction data have been measured, deliberately or inadvertently, the challenge is to sort the data into clusters that may represent relevant biological polystates. Here, this problem is addressed using a simple multi-factor clustering approach that classifies each data set using independent observables, thereby assigning each data set to the correct location in conformational space. This procedure is illustrated using two independent observables, unit-cell parameters and intensities, to cluster mixed-state data from chymotrypsinogen (ChTg) crystals. It is observed that the data populate an arc of the reaction trajectory as ChTg is converted into chymotrypsin. |
format | Online Article Text |
id | pubmed-8900820 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | International Union of Crystallography |
record_format | MEDLINE/PubMed |
spelling | pubmed-89008202022-03-29 A simple technique to classify diffraction data from dynamic proteins according to individual polymorphs Nguyen, Thu Phan, Kim L. Kozakov, Dima Gabelli, Sandra B. Kreitler, Dale F. Andrews, Lawrence C. Jakoncic, Jean Sweet, Robert M. Soares, Alexei S. Bernstein, Herbert J. Acta Crystallogr D Struct Biol Research Papers One often observes small but measurable differences in the diffraction data measured from different crystals of a single protein. These differences might reflect structural differences in the protein and may reveal the natural dynamism of the molecule in solution. Partitioning these mixed-state data into single-state clusters is a critical step that could extract information about the dynamic behavior of proteins from hundreds or thousands of single-crystal data sets. Mixed-state data can be obtained deliberately (through intentional perturbation) or inadvertently (while attempting to measure highly redundant single-crystal data). To the extent that different states adopt different molecular structures, one expects to observe differences in the crystals; each of the polystates will create a polymorph of the crystals. After mixed-state diffraction data have been measured, deliberately or inadvertently, the challenge is to sort the data into clusters that may represent relevant biological polystates. Here, this problem is addressed using a simple multi-factor clustering approach that classifies each data set using independent observables, thereby assigning each data set to the correct location in conformational space. This procedure is illustrated using two independent observables, unit-cell parameters and intensities, to cluster mixed-state data from chymotrypsinogen (ChTg) crystals. It is observed that the data populate an arc of the reaction trajectory as ChTg is converted into chymotrypsin. International Union of Crystallography 2022-02-18 /pmc/articles/PMC8900820/ /pubmed/35234141 http://dx.doi.org/10.1107/S2059798321013425 Text en © Thu Nguyen et al. 2022 https://creativecommons.org/licenses/by/4.0/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. |
spellingShingle | Research Papers Nguyen, Thu Phan, Kim L. Kozakov, Dima Gabelli, Sandra B. Kreitler, Dale F. Andrews, Lawrence C. Jakoncic, Jean Sweet, Robert M. Soares, Alexei S. Bernstein, Herbert J. A simple technique to classify diffraction data from dynamic proteins according to individual polymorphs |
title | A simple technique to classify diffraction data from dynamic proteins according to individual polymorphs |
title_full | A simple technique to classify diffraction data from dynamic proteins according to individual polymorphs |
title_fullStr | A simple technique to classify diffraction data from dynamic proteins according to individual polymorphs |
title_full_unstemmed | A simple technique to classify diffraction data from dynamic proteins according to individual polymorphs |
title_short | A simple technique to classify diffraction data from dynamic proteins according to individual polymorphs |
title_sort | simple technique to classify diffraction data from dynamic proteins according to individual polymorphs |
topic | Research Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8900820/ https://www.ncbi.nlm.nih.gov/pubmed/35234141 http://dx.doi.org/10.1107/S2059798321013425 |
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