Continuous flexibility analysis of SARS-CoV-2 spike prefusion structures
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Abstract
Using a new consensus-based image-processing approach together with principal component analysis, the flexibility and conformational dynamics of the SARS-CoV-2 spike in the prefusion state have been analysed. These studies revealed concerted motions involving the receptor-binding domain (RBD), N-terminal domain, and subdomains 1 and 2 around the previously characterized 1-RBD-up state, which have been modeled as elastic deformations. It is shown that in this data set there are not well defined, stable spike conformations, but virtually a continuum of states. An ensemble map was obtained with minimum bias, from which the extremes of the change along the direction of maximal variance were modeled by flexible fitting. The results provide a warning of the potential image-processing classification instability of these complicated data sets, which has a direct impact on the interpretability of the results.
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SciScore for 10.1101/2020.07.08.191072: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Most of the image processing done in this work has been done using Scipion framework (de la Rosa-Trevín et al., 2016) which is a public domain image processing framework freely available at url http://scipion.i2pc.es. Scipionsuggested: (SCIPION, RRID:SCR_016738)The former structure (PDB ID 6VSB) was fitted to the new map and refined using Coot (Emsley et al., 2010) and Phenix real space refine (Afonine et al., 2018). Cootsuggested: (Coot, RRID:SCR_014222)Validation metrics were computed to assess the geometry of the new hybrid model and its correlation with the map using Phenix … SciScore for 10.1101/2020.07.08.191072: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Most of the image processing done in this work has been done using Scipion framework (de la Rosa-Trevín et al., 2016) which is a public domain image processing framework freely available at url http://scipion.i2pc.es. Scipionsuggested: (SCIPION, RRID:SCR_016738)The former structure (PDB ID 6VSB) was fitted to the new map and refined using Coot (Emsley et al., 2010) and Phenix real space refine (Afonine et al., 2018). Cootsuggested: (Coot, RRID:SCR_014222)Validation metrics were computed to assess the geometry of the new hybrid model and its correlation with the map using Phenix comprehensive validation (cryo-EM), EMRinger algorithm (Barad et al., 2015), Q-score (Pintilie et al., 2020) and FSC-Q (Ramírez-Aportela et al., 2020a). Phenixsuggested: (Phenix, RRID:SCR_014224)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on pages 11, 12, 13, 14 and 22. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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