Op-cbio181027 2427..2433

Amaya Jiménez, Slavica Jonic, Tomas Majtner, Joaquı́n Otón, Jose Luis Vilas, David Maluenda, Javier Mota, Erney Ramı́rez-Aportela,Marta Martı́nez,Yaiza Rancel,Joan Segura,Ruben Sánchez-Garcı́a,Roberto Melero,Laura del Cano, Pablo Conesa, Lars Skjaerven,Roberto Marabini, Jose M. Carazo, Carlos Oscar S. Sorzano

semanticscholar(2019)

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摘要
Motivation: Cryo electron microscopy (EM) is currently one of the main tools to reveal the structural information of biological macromolecules. The re-construction of three-dimensional (3D) maps is typically carried out following an iterative process that requires an initial estimation of the 3D map to be refined in subsequent steps. Therefore, its determination is key in the quality of the final results, and there are cases in which it is still an open issue in single particle analysis (SPA). Small angle X-ray scattering (SAXS) is a well-known technique applied to structural biology. It is useful from small nanostructures up to macromolecular ensembles for its ability to obtain low resolution information of the biological sample measuring its X-ray scattering curve. These curves, together with further analysis, are able to yield information on the sizes, shapes and structures of the analyzed particles. Results: In this paper, we show how the low resolution structural information revealed by SAXS is very useful for the validation of EM initial 3D models in SPA, helping the following refinement process to obtain more accurate 3D structures. For this purpose, we approximate the initial map by pseudo-atoms and predict the SAXS curve expected for this pseudo-atomic structure. The match between the predicted and experimental SAXS curves is considered as a good sign of the correctness of the EM initial map. Availability and implementation: The algorithm is freely available as part of the Scipion 1.2 software at http://scipion.i2pc.es/. Contact: coss@cnb.csic.es VC The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com 2427 Bioinformatics, 35(14), 2019, 2427–2433 doi: 10.1093/bioinformatics/bty985 Advance Access Publication Date: 30 November 2018
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