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Elife . Allosteric modulation by the fatty acid site in the glycosylated SARS-CoV-2 spike

tetano

Editor, Senior Moderator
Elife


. 2025 Apr 10:13:RP97313.
doi: 10.7554/eLife.97313. Allosteric modulation by the fatty acid site in the glycosylated SARS-CoV-2 spike

A Sofia F Oliveira[SUP] 1 2 [/SUP], Fiona L Kearns[SUP] 3 [/SUP], Mia A Rosenfeld[SUP] 3 [/SUP], Lorenzo Casalino[SUP] 3 [/SUP], Lorenzo Tulli[SUP] 1 2 [/SUP], Imre Berger[SUP] 2 4 5 [/SUP], Christiane Schaffitzel[SUP] 4 [/SUP], Andrew D Davidson[SUP] 6 [/SUP], Rommie E Amaro[SUP] 7 [/SUP], Adrian J Mulholland[SUP] 1 2 [/SUP]



Affiliations
Abstract

The spike protein is essential to the SARS-CoV-2 virus life cycle, facilitating virus entry and mediating viral-host membrane fusion. The spike contains a fatty acid (FA) binding site between every two neighbouring receptor-binding domains. This site is coupled to key regions in the protein, but the impact of glycans on these allosteric effects has not been investigated. Using dynamical nonequilibrium molecular dynamics (D-NEMD) simulations, we explore the allosteric effects of the FA site in the fully glycosylated spike of the SARS-CoV-2 ancestral variant. Our results identify the allosteric networks connecting the FA site to functionally important regions in the protein, including the receptor-binding motif, an antigenic supersite in the N-terminal domain, the fusion peptide region, and another allosteric site known to bind heme and biliverdin. The networks identified here highlight the complexity of the allosteric modulation in this protein and reveal a striking and unexpected link between different allosteric sites. Comparison of the FA site connections from D-NEMD in the glycosylated and non-glycosylated spike revealed that glycans do not qualitatively change the internal allosteric pathways but can facilitate the transmission of the structural changes within and between subunits.

Keywords: SARS-CoV-2 spike; allostery; biochemistry; chemical biology; computational biology; fatty acids; glycans; nonequilibrium simulations; systems biology; viruses.

 
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