ArticleBiophysics and physicobiology2023
MOLASS: Software for automatic processing of matrix data obtained from small-angle X-ray scattering and UV-visible spectroscopy combined with size-exclusion chromatography.
Article in Biophysics and physicobiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
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- Structure of human DPPA3 bound to the UHRF1 PHD finger reveals its functional and structural differences from mouse DPPA3.Communications biology · 2024Article
- Adaptable SEC-SAXS data collection for higher quality structure analysis in solution.Protein science : a publication of the Protein Society · 2024Article
- Structure of full-length ERGIC-53 in complex with MCFD2 for cargo transport.Nature communications · 2024Article
- Heme-substituted protein assembly bridged by synthetic porphyrin: achieving controlled configuration while maintaining rotational freedom.RSC advances · 2024Article
- The two-step cargo recognition mechanism of heterotrimeric kinesin.EMBO reports · 2023Article
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- Structure of a putative immature form of a Rieske-type iron-sulfur protein in complex with zinc chloride.Communications chemistry · 2023Article
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5 authors.
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Abstract
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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