tetano
Editor, Senior Moderator
Comput Struct Biotechnol J
. 2024 May 24:23:2407-2417.
doi: 10.1016/j.csbj.2024.05.037. eCollection 2024 Dec. Dynamic expedition of leading mutations in SARS-CoV-2 spike glycoproteins
Muhammad Hasan[SUP] 1 2 [/SUP], Zhouyi He[SUP] 1 2 [/SUP], Mengqi Jia[SUP] 1 [/SUP], Alvin C F Leung[SUP] 1 3 [/SUP], Kathiresan Natarajan[SUP] 4 [/SUP], Wentao Xu[SUP] 1 [/SUP], Shanqi Yap[SUP] 1 [/SUP], Feng Zhou[SUP] 1 [/SUP], Shihong Chen[SUP] 1 [/SUP], Hailei Su[SUP] 5 [/SUP], Kaicheng Zhu[SUP] 1 [/SUP], Haibin Su[SUP] 1 2 [/SUP]
Affiliations
The continuous evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which caused the recent pandemic, has generated countless new variants with varying fitness. Mutations of the spike glycoprotein play a particularly vital role in shaping its evolutionary trajectory, as they have the capability to alter its infectivity and antigenicity. We present a time-resolved statistical method, Dynamic Expedition of Leading Mutations (deLemus), to analyze the evolutionary dynamics of the SARS-CoV-2 spike glycoprotein. The proposed L -index of the deLemus method is effective in quantifying the mutation strength of each amino acid site and outlining evolutionarily significant sites, allowing the comprehensive characterization of the evolutionary mutation pattern of the spike glycoprotein.
. 2024 May 24:23:2407-2417.
doi: 10.1016/j.csbj.2024.05.037. eCollection 2024 Dec. Dynamic expedition of leading mutations in SARS-CoV-2 spike glycoproteins
Muhammad Hasan[SUP] 1 2 [/SUP], Zhouyi He[SUP] 1 2 [/SUP], Mengqi Jia[SUP] 1 [/SUP], Alvin C F Leung[SUP] 1 3 [/SUP], Kathiresan Natarajan[SUP] 4 [/SUP], Wentao Xu[SUP] 1 [/SUP], Shanqi Yap[SUP] 1 [/SUP], Feng Zhou[SUP] 1 [/SUP], Shihong Chen[SUP] 1 [/SUP], Hailei Su[SUP] 5 [/SUP], Kaicheng Zhu[SUP] 1 [/SUP], Haibin Su[SUP] 1 2 [/SUP]
Affiliations
- PMID: 38882678
- PMCID: PMC11176665
- DOI: 10.1016/j.csbj.2024.05.037
The continuous evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which caused the recent pandemic, has generated countless new variants with varying fitness. Mutations of the spike glycoprotein play a particularly vital role in shaping its evolutionary trajectory, as they have the capability to alter its infectivity and antigenicity. We present a time-resolved statistical method, Dynamic Expedition of Leading Mutations (deLemus), to analyze the evolutionary dynamics of the SARS-CoV-2 spike glycoprotein. The proposed L -index of the deLemus method is effective in quantifying the mutation strength of each amino acid site and outlining evolutionarily significant sites, allowing the comprehensive characterization of the evolutionary mutation pattern of the spike glycoprotein.