Modelling conformational state dynamics and its role on infection for SARS-CoV-2 Spike protein variants

Teruel, Natália; Mailhot, Olivier; Najmanovich, Rafaël

doi:10.1371/journal.pcbi.1009286

Cited by 89 publications

(83 citation statements)

References 70 publications

(106 reference statements)

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“…A number of deletions and insertions exist in the Omicron S protein but are ignored here due to the difficulty in modelling the precise effect of deletions and insertions on protein structure. The structure of the open and closed states of the trimeric S Omicron protein as well as Omicron S in complex with ACE2 and 77 antibodies was prepared in the same manner as discussed in [15]. Dynamical Signatures (DS) and Vibrational Difference Scores (VDS) are based on normal mode analysis [16] and were introduced in [15] for the study of single point mutations and previous variants of the SARS-CoV-2 S protein.…”

Section: Methods Highlightsmentioning

confidence: 99%

Computational analysis of the effect of SARS-CoV-2 variant Omicron Spike protein mutations on dynamics, ACE2 binding and propensity for immune escape

Teruel

Crown

Bashton

et al. 2021

Preprint

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The recently reported Omicron (B.1.1.529) SARS-CoV-2 variant has a large number of mutations in the Spike (S) protein compared to previous variants. Here we evaluate the potential effect of Omicron S mutations on S protein dynamics and ACE2 binding as contributing factors to infectivity as well as propensity for immune escape. We define a consensus set of mutations from 77 sequences assigned as Omicron in GISAID as of November 25. We create structural models of the Omicron S protein in the open and closed states, as part of a complex with ACE2 and for each of 77 complexes of S bound to different antibodies with known structures. We have previously utilized Dynamical Signatures (DS) and the Vibrational Entropy Score (VDS) to evaluate the propensity of S variants to favour the open state. Here, we introduce the Binding Influence Score (BIS) to evaluate the influence of mutations on binding affinity based on the net gain or loss of interactions within the protein-protein interface. BIS shows excellent correlation with experimental data (Pearson correlation coefficient of 0.87) on individual mutations in the ACE2 interface for the Alpha, Beta, Gamma, Delta and Omicron variants combined. On the one hand, the DS of Omicron highly favours a more rigid open state and a more flexible closed state with the largest VDS of all variants to date, suggesting a large increase in the chances to interact with ACE2. On the other hand, the BIS shows that apart from N501Y, all other mutations in the interface reduce ACE2 binding affinity. VDS and BIS show opposing effects on the overall effectiveness of Omicron mutations to promote binding to ACE2 and therefore initiate infection. To evaluate the propensity for immune escape we calculated the net change of favourable and unfavourable interactions within each S-antibody interface. The net change of interactions shows a positive score (a net increase of favourable interactions and decrease of unfavourable ones) for 41 out of 77 antibodies, a nil score for 15 and a negative score for 21 antibodies. Therefore, in only 28% of S-antibody complexes (21/77) we predict some level of immune escape due to a weakening of the interactions with Omicron S. Considering that most antibody epitopes and the mutations are within the S-ACE2 interface our results suggest that mutations within the RBD of Omicron may give rise to only partial immune escape, which comes at the expense of reduced ACE2 binding affinity. However, this reduced ACE2 affinity appears to have been offset by increasing the occupancy of the open state of the Spike protein.

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Section: Methods Highlightsmentioning

confidence: 99%

Computational analysis of the effect of SARS-CoV-2 variant Omicron Spike protein mutations on dynamics, ACE2 binding and propensity for immune escape

Teruel

Crown

Bashton

et al. 2021

Preprint

Self Cite

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“…Different computational approaches have focused on the SARS-CoV-2 spike, and the scientific community is actively working on the subject. For instance, coarse-grained modeling was employed to characterize binding to ACE2 and antibodies [40, 41], molecular docking to predict molecular inhibitors [14, 38, 39], molecular dynamics to design peptides against the spike [42], and normal mode analysis to explore conformational states [47]. QM modeling using Density Functional Theory has been employed to analyze functional domains of the Spike protein [44] and to simulate the spike electronic structure to find hydrogen bonds determining its interactions.…”

Section: Introductionmentioning

confidence: 99%

Anticipating future SARS-CoV-2 variants of concern through ab initio quantum mechanical modeling

Zaccaria

Genovese

Farzan

et al. 2021

Preprint

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Evolved SARS-CoV-2 variants are currently challenging the efficacy of first-generation vaccines, largely through the emergence of spike protein mutants. Among these variants, Delta is presently the most concerning. We employ an ab initio quantum mechanical model based on Density Functional Theory to characterize the spike protein Receptor Binding Domain (RBD) interaction with host cells and gain mechanistic insight into SARS-CoV-2 evolution. The approach is illustrated via a detailed investigation of the role of the E484K RBD mutation, a signature mutation of the Beta and Gamma variants. The simulation is employed to: predict the depleting effect of the E484K mutation on binding the RBD with select antibodies; identify residue E484 as a weak link in the original interaction with the human receptor hACE2; and describe SARS-CoV-2 Wuhan strand binding to the bat Rhinolophus macrotis ACE2 as more optimized than the human counterpart. Finally, we predict the hACE2 binding efficacy of a hypothetical E484K mutation added to the Delta variant RBD, identifying a potential future variant of concern. Results can be generalized to other mutations, and provide useful information to complement existing experimental datasets of the interaction between randomly generated libraries of hACE2 and viral spike mutants. We argue that ab initio modeling is at the point of being aptly employed to inform and predict events pertinent to viral and general evolution.

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“…Its role in modulating viral infectivity and antigenicity still needs to be elucidated. Similarly to E484K, E484Q was associated with a 10-fold decrease in neutralization efficiency by vaccine-induced antibodies, suggesting a role (albeit moderate) as an immune escape mutation ( 51 ). No synergistic reduction in neutralization efficiency was observed when E484Q was combined with L452R ( 51 ).…”

Section: Resultsmentioning

confidence: 99%

SARS-CoV-2 Variants and Their Relevant Mutational Profiles: Update Summer 2021

et al. 2021

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Since the emergence of SARS-CoV-2, several recurrent mutations, particularly in the spike protein, arose during human-to-human transmission or spillover events between humans and animals, generating distinct worrisome variants of concern (VOCs) or of interest (VOIs), designated as such due to their clinical and diagnostic impacts. Characterizing these variants and their related mutations is important in tracking SAR-CoV-2 evolution and understanding the efficacy of vaccines and therapeutics based on monoclonal antibodies, convalescent-phase sera, and direct antivirals.

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Modelling conformational state dynamics and its role on infection for SARS-CoV-2 Spike protein variants

Cited by 89 publications

References 70 publications

Computational analysis of the effect of SARS-CoV-2 variant Omicron Spike protein mutations on dynamics, ACE2 binding and propensity for immune escape

Computational analysis of the effect of SARS-CoV-2 variant Omicron Spike protein mutations on dynamics, ACE2 binding and propensity for immune escape

Anticipating future SARS-CoV-2 variants of concern through ab initio quantum mechanical modeling

SARS-CoV-2 Variants and Their Relevant Mutational Profiles: Update Summer 2021

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