| アイテムタイプ |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2024-05-10 |
| タイトル |
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タイトル |
MOLASS: Software for automatic processing of matrix data obtained from small-angle X-ray scattering and UV$2013visible spectroscopy combined with size-exclusion chromatography |
| 言語 |
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言語 |
eng |
| キーワード |
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主題Scheme |
Other |
|
主題 |
SEC-SAXS |
| キーワード |
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主題Scheme |
Other |
|
主題 |
automatic data analysis |
| キーワード |
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主題Scheme |
Other |
|
主題 |
concentration dependence |
| キーワード |
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主題Scheme |
Other |
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主題 |
Moore-Penrose pseudo-inverse matrix |
| 資源タイプ |
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資源タイプ |
data paper |
| アクセス権 |
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アクセス権 |
open access |
| 著者 |
米澤, 健人
Takahashi, Masatsuyo
Yatabe, Keiko
Nagatani, Yasuko
Shimizu, Nobutaka
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| 抄録 |
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内容記述タイプ |
Abstract |
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内容記述 |
Recent small-angle X-ray scattering (SAXS) for biological macromolecules (BioSAXS) is generally combined with size-exclusion chromatography (SEC-SAXS) at synchrotron facilities worldwide. For SEC-SAXS analysis, the final scattering profile for the target molecule is calculated from a large volume of continuously collected data. It would be ideal to automate this process; however, several complex problems exist regarding data measurement and analysis that have prevented automation. Here, we developed the analytical software MOLASS (Matrix Optimization with Low-rank factorization for Automated analysis of SEC-SAXS) to automatically calculate the final scattering profiles for solution structure analysis of target molecules. In this paper, the strategies for automatic analysis of SEC-SAXS data are described, including correction of baseline-drift using a low percentile method, optimization of peak decompositions composed of multiple scattering components using modified Gaussian fitting against the chromatogram, and rank determination for extrapolation to infinite dilution. In order to easily calculate each scattering component, the Moore-Penrose pseudo-inverse matrix is adopted as a basic calculation. Furthermore, this analysis method, in combination with UV$2013visible spectroscopy, led to better results in terms of accuracy in peak decomposition. Therefore, MOLASS will be able to smoothly suggest to users an accurate scattering profile for the subsequent structural analysis. |
| 書誌情報 |
en : Biophysics and Physicobiology
巻 20,
号 1,
発行日 2023-02-04
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| 出版者 |
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出版者 |
Biophysical Society of Japan |
| ISSN |
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収録物識別子タイプ |
EISSN |
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収録物識別子 |
2189-4779 |
| 出版者版DOI |
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関連タイプ |
isIdenticalTo |
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識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.2142/biophysico.bppb-v20.0001 |
| 出版者版URI |
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関連タイプ |
isIdenticalTo |
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識別子タイプ |
URI |
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関連識別子 |
https://www.jstage.jst.go.jp/article/biophysico/20/1/20_e200001/_article/-char/ja |
| 権利 |
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権利情報Resource |
https://creativecommons.org/licenses/by-nc-sa/4.0/ |
|
権利情報 |
c 2023 THE BIOPHYSICAL SOCIETY OF JAPAN. This article is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-sa/4.0/. |
| 著者版フラグ |
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出版タイプ |
VoR |
fulltext (3.8 MB)
