tetano
Editor, Senior Moderator
J Biomol Struct Dyn
. 2020 Aug 4;1-8.
doi: 10.1080/07391102.2020.1802338. Online ahead of print.
Deciphering the protein motion of S1 subunit in SARS-CoV-2 spike glycoprotein through integrated computational methods
Hao Tian[SUP] 1 [/SUP], Peng Tao[SUP] 1 [/SUP]
Affiliations
Abstract
The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a major worldwide public health emergency that has infected over 8 million people. Spike glycoprotein, especially the partially open state of S1 subunit, in SARS-CoV-2 is considered vital for its infection with human host cell. However, the mechanism elucidating the transition from the closed state to the partially open state still remains unclear. In this study, we applied a series of computational methods, including Markov state model, transition path theory and random forest to analyze the S1 motion. Our results showed a promising complete conformational movement of the receptor-binding domain, from buried, partially open, to detached states. We also estimated the transition probability among these states. Based on the asymmetry in both the dynamics behavior and the accumulated alpha carbon (Cα) importance, we further suggested a relation among chains in the trimer spike protein, which leads to a deeper understanding on protein motions of the S1 subunit. Communicated by Ramaswamy H. Sarma.
Keywords: Markov state model; SARS-CoV-2; random forest; spike glycoprotein; transition path theory.
. 2020 Aug 4;1-8.
doi: 10.1080/07391102.2020.1802338. Online ahead of print.
Deciphering the protein motion of S1 subunit in SARS-CoV-2 spike glycoprotein through integrated computational methods
Hao Tian[SUP] 1 [/SUP], Peng Tao[SUP] 1 [/SUP]
Affiliations
- PMID: 32746720
- DOI: 10.1080/07391102.2020.1802338
Abstract
The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a major worldwide public health emergency that has infected over 8 million people. Spike glycoprotein, especially the partially open state of S1 subunit, in SARS-CoV-2 is considered vital for its infection with human host cell. However, the mechanism elucidating the transition from the closed state to the partially open state still remains unclear. In this study, we applied a series of computational methods, including Markov state model, transition path theory and random forest to analyze the S1 motion. Our results showed a promising complete conformational movement of the receptor-binding domain, from buried, partially open, to detached states. We also estimated the transition probability among these states. Based on the asymmetry in both the dynamics behavior and the accumulated alpha carbon (Cα) importance, we further suggested a relation among chains in the trimer spike protein, which leads to a deeper understanding on protein motions of the S1 subunit. Communicated by Ramaswamy H. Sarma.
Keywords: Markov state model; SARS-CoV-2; random forest; spike glycoprotein; transition path theory.