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

  1. Marco Zaccaria
  2. Luigi Genovese
  3. William Dawson
  4. Viviana Cristiglio
  5. Takahito Nakajima
  6. Welkin Johnson
  7. Michael Farzan
  8. Babak Momeni

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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.

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  1. Version published to 10.1093/pnasnexus/pgac180
  2. ScreenIT

    SciScore for 10.1101/2021.11.25.470044: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Structure relaxations are performed by optimizing the crystal geometry with the OpenMM package using the AMBER FF14SB force field [28].
    OpenMM
    suggested: (OpenMM, RRID:SCR_000436)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    On the other side, the abundance of data for SARS-CoV-2 has provided an opportunity to test and validate the potentials and limitations of ab initio modeling. This, in conjunction with the maturity of large-scale quantum mechanical calculations, represents a unique opportunity to employ full QM calculations to uncover the interaction mechanisms which would be difficult or impossible to investigate otherwise. We show that ab initio modeling provides insights useful for comparison with experimental data, supporting its capability to offer predictive power for inter-molecular interactions of biological relevance. Research paradigms on large biomolecules investigation, in various domains, can now effectively include QM data. Model limitations: The model, despite its first-principles origin, is based on assumptions. First, the quantities we are investigating, while representing the binding energy, do not directly manifest experimental results. A closely-related quantity may be the off-rate dissociation constant, that can be inversely proportional to the structures’ stability. However, to correctly evaluate such terms, the systems’ free energies must be considered, which would require dynamic structural investigations. Additionally, the mutated structures are based on reference structures whose 3D conformation may in principle be altered by a given mutation. Therefore, in the absence of confirmed crystal structures, these structures can only be interpreted as virtual best guesses. ...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on page 24. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

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  3. Version published to 10.1101/2021.11.25.470044v1 on bioRxiv