Quantum mechanical model offers insights into SARS-CoV-2 evolution

The spike protein receptor-binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has undergone several mutations since the virus emerged in late 2019. The mutations to the SARS-CoV-2 RBD have given rise to several new variants of concern (VOCs) such as the Alpha, Beta, Gamma, and Delta variants that threaten to mitigate the effect of global vaccination campaigns against SARS-CoV-2. Gaining mechanistic insights into these RBD mutations of SARS-CoV-2 could help predict the emergence of new VOCs and prevent their spread.

Study: Anticipating future SARS-CoV-2 variants of concern through ab initio quantum mechanical modeling. Image Credit: Corona Borealis Studio/ShutterstockStudy: Anticipating future SARS-CoV-2 variants of concern through ab initio quantum mechanical modeling. Image Credit: Corona Borealis Studio/Shutterstock

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Study design

In a pre-print study published in the bioRxiv* server, a team of researchers used an ab initio full quantum mechanical (QM) model to characterize the spike protein RBD interactions with host cells and gain mechanistic insights into SARS-CoV-2 evolution. They performed ab initio QM modeling of the binding of the SARS-CoV-2 spike RBD with select substrates, focusing on the E484K RBD mutation, a typical signature mutation of the Beta and Gamma variants. They simulated biological macromolecules of sizes large enough to represent relevant SARS-CoV-2 processes like the binding of the SARS-CoV-2 spike RBD with select substrates.

The researchers also analyzed some known SARS-CoV-2 adaptations, such as the role of the E484K mutation in the evasion of neutralizing antibodies (nAbs) C121 and C144; the spike interaction with the bat host Rhinolophus macrotis angiotensin-converting enzyme 2 (ACE2) (macACE2); and the Delta variant spike interaction with hACE2. Lastly, the researchers used this model to predict the effect of a hypothetical mutation of the SARS-CoV-2 Delta variant spike RBD in the binding to human cells.

Findings

The researchers characterized the chemical interaction of the nAbs with the original Wuhan spike and the mutated E484K one. They identified that while K444, Y449, F486, 155 Y489, and Q493 residues interacted with C121, the individual contribution of E484 residue to this interaction was roughly 50% of the total. After the E484 mutation was applied, there was a substantial decrease of approximately 25% of total binding energy, indicating a loss of chemical interaction between nAb C121 and E484K.

The ab initio model showed that E484 is the main spike interactor with nAb C121 and is essential for the binding event, and therefore neutralization. A targeted mutation in E484 residue substantially affects binding, resulting in a loss of interaction with nAbs C121 and C144. This evidence also suggests that mutations in E484 are generating selective pressure for the virus to find alternatives to the original phenotype.

The bat Rhinolophus macrotis is a host species more adapted to SARS-CoV-2 interaction. On examining the sequences of hACE2 and macACE2, residue K31 emerged as the principal interactor with E484 residue. In the macACE2, the other residue K35 exerts an attractive electrostatic force on E484, which in hACE2 is replaced by glutamic acid. Therefore, the ab initio model highlights a strong contrast between human and bat receptors. This finding suggests that E484K mutation is part of the viral adaptation specific to the human host.

The experimentally validated spike-ACE2 3D structure of the highly infectious Delta variant is unavailable. The researchers generated a virtual crystal structure to represent the Delta variant in combination with hACE2 by substituting its RBD mutations (L452R and T478K) into the Wuhan spike crystal structure. When the binding of the Delta-hACE2 system was examined after introducing this hypothetical mutation, the ab intio simulation results showed that E484K is compatible with the Delta variant and further strengthens the overall binding of its spike protein to hACE2. 

Conclusion

The massive impact of the coronavirus disease 2019 (COVID-19) pandemic on global health and socioeconomic stability makes it crucial to increase the readiness to handle emerging SARS-CoV-2 spike protein mutants as these variants challenge the efficacy of first-generation vaccines.

With the availability of biomolecular and structural data on SARS-CoV-2, researchers have an opportunity to test and validate this vast data using the ab initio modeling and gain mechanistic insights into SARS-CoV-2 evolution. Due to their unbiased and agnostic nature, these models could be applied to other biological systems. The results can be generalized to other mutations to predict events pertinent to viral and general evolution.

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Journal references:

Article Revisions

  • May 8 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.

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