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MOLASS: Software for automatic processing of matrix data obtained from small-angle X-ray scattering and UV–visible spectroscopy combined with size-exclusion chromatography

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...

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Autores principales: Yonezawa, Kento, Takahashi, Masatsuyo, Yatabe, Keiko, Nagatani, Yasuko, Shimizu, Nobutaka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Biophysical Society of Japan 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10203098/
https://www.ncbi.nlm.nih.gov/pubmed/37229310
http://dx.doi.org/10.2142/biophysico.bppb-v20.0001
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author Yonezawa, Kento
Takahashi, Masatsuyo
Yatabe, Keiko
Nagatani, Yasuko
Shimizu, Nobutaka
author_facet Yonezawa, Kento
Takahashi, Masatsuyo
Yatabe, Keiko
Nagatani, Yasuko
Shimizu, Nobutaka
author_sort Yonezawa, Kento
collection PubMed
description 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–visible 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.
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spelling pubmed-102030982023-05-24 MOLASS: Software for automatic processing of matrix data obtained from small-angle X-ray scattering and UV–visible spectroscopy combined with size-exclusion chromatography Yonezawa, Kento Takahashi, Masatsuyo Yatabe, Keiko Nagatani, Yasuko Shimizu, Nobutaka Biophys Physicobiol Database and Computer Program 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–visible 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. The Biophysical Society of Japan 2023-01-07 /pmc/articles/PMC10203098/ /pubmed/37229310 http://dx.doi.org/10.2142/biophysico.bppb-v20.0001 Text en 2023 THE BIOPHYSICAL SOCIETY OF JAPAN https://creativecommons.org/licenses/by-nc-sa/4.0/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/.
spellingShingle Database and Computer Program
Yonezawa, Kento
Takahashi, Masatsuyo
Yatabe, Keiko
Nagatani, Yasuko
Shimizu, Nobutaka
MOLASS: Software for automatic processing of matrix data obtained from small-angle X-ray scattering and UV–visible spectroscopy combined with size-exclusion chromatography
title MOLASS: Software for automatic processing of matrix data obtained from small-angle X-ray scattering and UV–visible spectroscopy combined with size-exclusion chromatography
title_full MOLASS: Software for automatic processing of matrix data obtained from small-angle X-ray scattering and UV–visible spectroscopy combined with size-exclusion chromatography
title_fullStr MOLASS: Software for automatic processing of matrix data obtained from small-angle X-ray scattering and UV–visible spectroscopy combined with size-exclusion chromatography
title_full_unstemmed MOLASS: Software for automatic processing of matrix data obtained from small-angle X-ray scattering and UV–visible spectroscopy combined with size-exclusion chromatography
title_short MOLASS: Software for automatic processing of matrix data obtained from small-angle X-ray scattering and UV–visible spectroscopy combined with size-exclusion chromatography
title_sort molass: software for automatic processing of matrix data obtained from small-angle x-ray scattering and uv–visible spectroscopy combined with size-exclusion chromatography
topic Database and Computer Program
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10203098/
https://www.ncbi.nlm.nih.gov/pubmed/37229310
http://dx.doi.org/10.2142/biophysico.bppb-v20.0001
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