Conformational transition of SARS-CoV-2 spike glycoprotein between its closed and open states

Mert Gur*, Elhan Taka, Sema Zeynep Yilmaz, Ceren Kilinc, Umut Aktas, Mert Golcuk

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

88 Citations (Scopus)


In 2020, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected millions of people worldwide and caused the coronavirus disease 2019 (COVID-19). Spike (S) glycoproteins on the viral membrane bind to ACE2 receptors on the host cell membrane and initiate fusion, and S protein is currently among the primary drug target to inhibit viral entry. The S protein can be in a receptor inaccessible (closed) or accessible (open) state based on down and up positions of its receptor-binding domain (RBD), respectively. However, conformational dynamics and the transition pathway between closed to open states remain unexplored. Here, we performed all-atom molecular dynamics (MD) simulations starting from closed and open states of the S protein trimer in the presence of explicit water and ions. MD simulations showed that RBD forms a higher number of interdomain interactions and exhibits lower mobility in its down position than its up position. MD simulations starting from intermediate conformations between the open and closed states indicated that RBD switches to the up position through a semi-open intermediate that potentially reduces the free energy barrier between the closed and open states. Free energy landscapes were constructed, and a minimum energy pathway connecting the closed and open states was proposed. Because RBD-ACE2 binding is compatible with the semi-open state, but not with the closed state of the S protein, we propose that the formation of the intermediate state is a prerequisite for the host cell recognition.

Original languageEnglish
Article number075101
JournalJournal of Chemical Physics
Issue number7
Publication statusPublished - 21 Aug 2020

Bibliographical note

Publisher Copyright:
© 2020 Author(s).


We thank Kadir Diri for his technical support at UHeM and Ahmet Yildiz (UC Berkeley) for scientific discussions. We gratefully acknowledge the support of the National Center of High Performance Computing (UHeM) at ITU, the COVID-19 HPC Consortium (Grant No. TG-MCB200070), and The Extreme Science and Engineering Discovery Environment (XSEDE).

FundersFunder number
National Center of High Performance Computing
International Technological University


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