Probing the mutational landscape of the SARS-CoV-2 spike protein via quantum mechanical modeling of crystallographic structures

Author:

Zaccaria Marco1,Genovese Luigi2ORCID,Dawson William3ORCID,Cristiglio Viviana4ORCID,Nakajima Takahito3ORCID,Johnson Welkin1,Farzan Michael5,Momeni Babak1ORCID

Affiliation:

1. Department of Biology, Boston College , Chestnut Hill, MA 02467 , USA

2. Université Grenoble Alpes, CEA, INAC-MEM, L_Sim , 38000 Grenoble , France

3. RIKEN Center for Computational Science, 7-1-26, Minatojima-minamimi-machi, Chuo-ku, Kobe , Hyogo 650-0047 , Japan

4. Institute Laue Langevin , 71 Av. des Martyrs, 38000 Grenoble , France

5. Department of Immunology and Microbiology, The Scripps Research Institute , Jupiter, FL 33458 , USA

Abstract

Abstract We employ a recently developed complexity-reduction quantum mechanical (QM-CR) approach, based on complexity reduction of density functional theory calculations, to characterize the interactions of the SARS-CoV-2 spike receptor binding domain (RBD) with ACE2 host receptors and antibodies. QM-CR operates via ab initio identification of individual amino acid residue’s contributions to chemical binding and leads to the identification of the impact of point mutations. Here, we especially focus on the E484K mutation of the viral spike protein. We find that spike residue 484 hinders the spike's binding to the human ACE2 receptor (hACE2). In contrast, the same residue is beneficial in binding to the bat receptor Rhinolophus macrotis ACE2 (macACE2). In agreement with empirical evidence, QM-CR shows that the E484K mutation allows the spike to evade categories of neutralizing antibodies like C121 and C144. The simulation also shows how the Delta variant spike binds more strongly to hACE2 compared to the original Wuhan strain, and predicts that a E484K mutation can further improve its binding. Broad agreement between the QM-CR predictions and experimental evidence supports the notion that ab initio modeling has now reached the maturity required to handle large intermolecular interactions central to biological processes.

Funder

French National Computing Resources

Richard and Susan Smith Family Foundation

Publisher

Oxford University Press (OUP)

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