> Details

Melero, Roberto; Sorzano, Carlos Oscar S.; Foster, Brent; Vilas, José-Luis; Martínez, Marta; Marabini, Roberto; Ramírez-Aportela, Erney; Sanchez-Garcia, Ruben; Herreros, David; del Caño, Laura; Losana, Patricia; Fonseca-Reyna, Yunior C.; Conesa, Pablo; Wrapp, Daniel; Chacon, Pablo; McLellan, Jason S.; Tagare, Hemant D.; Carazo, Jose-Maria

Continuous flexibility analysis of SARS-CoV-2 spike prefusion structures

Reference
management

Bookmarks

Remove from
bookmarks

Share this on Whatsapp

Close

Bookmarks



You can manage bookmarks using lists, please log in to your user account for this.
  • Media type: E-Article
  • Title: Continuous flexibility analysis of SARS-CoV-2 spike prefusion structures
  • Contributor: Melero, Roberto; Sorzano, Carlos Oscar S.; Foster, Brent; Vilas, José-Luis; Martínez, Marta; Marabini, Roberto; Ramírez-Aportela, Erney; Sanchez-Garcia, Ruben; Herreros, David; del Caño, Laura; Losana, Patricia; Fonseca-Reyna, Yunior C.; Conesa, Pablo; Wrapp, Daniel; Chacon, Pablo; McLellan, Jason S.; Tagare, Hemant D.; Carazo, Jose-Maria
  • Published: International Union of Crystallography (IUCr), 2020
  • Published in: IUCrJ, 7 (2020) 6, Seite 1059-1069
  • Language: Without Specification
  • DOI: 10.1107/s2052252520012725
  • ISSN: 2052-2525
  • Origination:
  • Footnote:
  • Description: 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.
  • Access State: Open Access