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Automatic building of protein atomic models from cryo-EM density maps using residue co-evolution

Guillaume Bouvier, Benjamin Bardiaux, Riccardo Pellarin, Chiara Rapisarda, Michael Nilges
doi: https://doi.org/10.1101/2020.01.03.893669
Guillaume Bouvier
†Structural Bioinformatics Unit, Department of Structural Biology and Chemistry; CNRS UMR 3528; C3BI, CNRS USR 3756; Institut Pasteur, Paris, France
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  • For correspondence: guillaume.bouvier@pasteur.fr
Benjamin Bardiaux
†Structural Bioinformatics Unit, Department of Structural Biology and Chemistry; CNRS UMR 3528; C3BI, CNRS USR 3756; Institut Pasteur, Paris, France
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Riccardo Pellarin
†Structural Bioinformatics Unit, Department of Structural Biology and Chemistry; CNRS UMR 3528; C3BI, CNRS USR 3756; Institut Pasteur, Paris, France
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Chiara Rapisarda
‡CNRS UMR 5234 Microbiologie Fondamentale et Pathogénicité, Bordeaux, France
¶Institut Européen de Chimie et Biologie, University of Bordeaux, Pessac, France
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Michael Nilges
†Structural Bioinformatics Unit, Department of Structural Biology and Chemistry; CNRS UMR 3528; C3BI, CNRS USR 3756; Institut Pasteur, Paris, France
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Abstract

Electron cryo-microscopy (cryo-EM) has emerged as a powerful method to obtain three-dimensional (3D) structures of macromolecular complexes at atomic or near-atomic resolution. However, de novo building of atomic models from near-atomic resolution (3-5 Å) cryo-EM density maps is a challenging task, in particular since poorly resolved side-chain densities hamper sequence assignment by automatic procedures at a lower resolution. Furthermore, segmentation of EM density maps into individual subunits remains a difficult problem when no three-dimensional structures of these subunits exist, or when significant conformational changes occur between the isolated and complexed form of the subunits. To tackle these issues, we have developed a graph-based method to thread most of the C-α trace of the protein backbone into the EM density map. The EM density is described as a weighted graph such that the resulting minimum spanning tree encompasses the high-density regions of the map. A pruning algorithm cleans the tree and finds the most probable positions of the C-α atoms, using side-chain density when available, as a collection of C-α trace fragments. By complementing experimental EM maps with contact predictions from sequence co-evolutionary information, we demonstrate that our approach can correctly segment EM maps into individual subunits and assign amino acids sequence to backbone traces to generate full-atom models.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted January 03, 2020.
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Automatic building of protein atomic models from cryo-EM density maps using residue co-evolution
Guillaume Bouvier, Benjamin Bardiaux, Riccardo Pellarin, Chiara Rapisarda, Michael Nilges
bioRxiv 2020.01.03.893669; doi: https://doi.org/10.1101/2020.01.03.893669
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Automatic building of protein atomic models from cryo-EM density maps using residue co-evolution
Guillaume Bouvier, Benjamin Bardiaux, Riccardo Pellarin, Chiara Rapisarda, Michael Nilges
bioRxiv 2020.01.03.893669; doi: https://doi.org/10.1101/2020.01.03.893669

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