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Computational epitope map of SARS-CoV-2 spike protein

  • Abstract The primary immunological target of COVID-19 vaccines is the SARS-CoV-2 spike (S) protein. S is exposed on the viral surface and mediates viral entry into the host cell. To identify possible antibody binding sites, we performed multi-microsecond molecular dynamics simulations of a 4.1 million atom system containing a patch of viral membrane with four full-length, fully glycosylated and palmitoylated S proteins. By mapping steric accessibility, structural rigidity, sequence conservation, and generic antibody binding signatures, we recover known epitopes on S and reveal promising epitope candidates for structure-based vaccine design. We find that the extensive and inherently flexible glycan coat shields a surface area larger than expected from static structures, highlighting the importance of structural dynamics. The protective glycan shield and the high flexibility of its hinges give the stalk overall low epitope scores. Our computational epitope-mapping procedure is general and should thus prove useful for other viral envelope proteins whose structures have been characterized. Author summary The SARS-CoV-2 virus has caused a global health crisis. The spike protein exposed at its surface is key for infection and the primary antibody target. However, spike is covered by highly mobile glycan molecules that could impair antibody binding. To identify accessible epitopes, we performed molecular dynamics simulations of an atomistic model of glycosylated spike embedded in a membrane. By combining extensive simulations with bioinformatics analyses, we recovered known antibody binding sites and identified several epitope candidates as targets for further vaccine development.

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Verfasserangaben:Mateusz SikoraORCiD, Sören von BülowORCiDGND, Florian E. C. BlancORCiD, Michael GechtORCiDGND, Roberto CovinoORCiD, Gerhard HummerORCiD
URN:urn:nbn:de:hebis:30:3-732800
DOI:https://doi.org/10.1371/journal.pcbi.1008790
ISSN:1553-7358
Titel des übergeordneten Werkes (Englisch):PLOS Computational Biology
Verlag:Public Library of Science
Verlagsort:San Francisco, Calif.
Dokumentart:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Veröffentlichung (online):01.04.2021
Datum der Erstveröffentlichung:01.04.2021
Veröffentlichende Institution:Universitätsbibliothek Johann Christian Senckenberg
Datum der Freischaltung:14.06.2023
Jahrgang:17
Ausgabe / Heft:4
Seitenzahl:16
Erste Seite:1
Letzte Seite:16
HeBIS-PPN:510041043
Institute:Physik
Wissenschaftliche Zentren und koordinierte Programme / Frankfurt Institute for Advanced Studies (FIAS)
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Sammlungen:Universitätspublikationen
Lizenz (Deutsch):License LogoCreative Commons - Namensnennung 4.0