A model of the SARS-CoV-2 Spike protein surface has revealed vulnerabilities that researchers say could inform the development of COVID-19 vaccines.
A new, detailed surface model of the SARS-CoV-2 Spike (S) protein has revealed previously unknown vulnerabilities that could inform the development of vaccines. The study was conducted at the Max Planck Institute of Biophysics, Germany.
According to the researchers, a key feature of SARS-CoV-2 is its protein S, which extends from its surface and allows it to target and infect human cells. Extensive research has resulted in detailed static models of the S protein, but these models do not record the flexibility of the protein itself or the movements of protective glycans – sugar molecule chains – that cover it.
To support the development of vaccines, the team aimed to identify new potential target sites on the surface of protein S. To do this, they developed molecular dynamics simulations that capture the complete structure of protein S and its movements in a realistic environment.
These simulations show that the glucans in protein S act as a dynamic shield that helps the virus evade the human immune system. Similar to car windshield wipers, glucans cover almost the entire surface of protein S by flipping back and forth, although their coverage is minimal at any given time.
Combining dynamic S protein simulations with bioinformatics analysis, the researchers identified spots on the surface of proteins that are less protected by glucan shields. Some of the sites found have been identified in previous research, but some are new. The vulnerability of many of these new sites has been confirmed by other research teams in subsequent laboratory experiments.
“We are in a phase of a pandemic due to the emergence of new variants of SARS-CoV-2, with mutations particularly concentrated in the S protein,” said lead researcher Mateusz Sikora. “Our approach can support the design of vaccines and therapeutic antibodies, especially when established methods are struggling.”
The researchers say the method developed for this study could also be used to identify potential vulnerabilities in other viral proteins.
The study was published in Computational Biology PLOS.