Cargando…

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

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 oper...

Descripción completa

Detalles Bibliográficos
Autores principales: Zaccaria, Marco, Genovese, Luigi, Dawson, William, Cristiglio, Viviana, Nakajima, Takahito, Johnson, Welkin, Farzan, Michael, Momeni, Babak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9802038/
https://www.ncbi.nlm.nih.gov/pubmed/36712320
http://dx.doi.org/10.1093/pnasnexus/pgac180
_version_ 1784861609044213760
author Zaccaria, Marco
Genovese, Luigi
Dawson, William
Cristiglio, Viviana
Nakajima, Takahito
Johnson, Welkin
Farzan, Michael
Momeni, Babak
author_facet Zaccaria, Marco
Genovese, Luigi
Dawson, William
Cristiglio, Viviana
Nakajima, Takahito
Johnson, Welkin
Farzan, Michael
Momeni, Babak
author_sort Zaccaria, Marco
collection PubMed
description 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.
format Online
Article
Text
id pubmed-9802038
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-98020382023-01-26 Probing the mutational landscape of the SARS-CoV-2 spike protein via quantum mechanical modeling of crystallographic structures Zaccaria, Marco Genovese, Luigi Dawson, William Cristiglio, Viviana Nakajima, Takahito Johnson, Welkin Farzan, Michael Momeni, Babak PNAS Nexus Biological, Health, and Medical Sciences 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. Oxford University Press 2022-09-01 /pmc/articles/PMC9802038/ /pubmed/36712320 http://dx.doi.org/10.1093/pnasnexus/pgac180 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of National Academy of Sciences. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Biological, Health, and Medical Sciences
Zaccaria, Marco
Genovese, Luigi
Dawson, William
Cristiglio, Viviana
Nakajima, Takahito
Johnson, Welkin
Farzan, Michael
Momeni, Babak
Probing the mutational landscape of the SARS-CoV-2 spike protein via quantum mechanical modeling of crystallographic structures
title Probing the mutational landscape of the SARS-CoV-2 spike protein via quantum mechanical modeling of crystallographic structures
title_full Probing the mutational landscape of the SARS-CoV-2 spike protein via quantum mechanical modeling of crystallographic structures
title_fullStr Probing the mutational landscape of the SARS-CoV-2 spike protein via quantum mechanical modeling of crystallographic structures
title_full_unstemmed Probing the mutational landscape of the SARS-CoV-2 spike protein via quantum mechanical modeling of crystallographic structures
title_short Probing the mutational landscape of the SARS-CoV-2 spike protein via quantum mechanical modeling of crystallographic structures
title_sort probing the mutational landscape of the sars-cov-2 spike protein via quantum mechanical modeling of crystallographic structures
topic Biological, Health, and Medical Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9802038/
https://www.ncbi.nlm.nih.gov/pubmed/36712320
http://dx.doi.org/10.1093/pnasnexus/pgac180
work_keys_str_mv AT zaccariamarco probingthemutationallandscapeofthesarscov2spikeproteinviaquantummechanicalmodelingofcrystallographicstructures
AT genoveseluigi probingthemutationallandscapeofthesarscov2spikeproteinviaquantummechanicalmodelingofcrystallographicstructures
AT dawsonwilliam probingthemutationallandscapeofthesarscov2spikeproteinviaquantummechanicalmodelingofcrystallographicstructures
AT cristiglioviviana probingthemutationallandscapeofthesarscov2spikeproteinviaquantummechanicalmodelingofcrystallographicstructures
AT nakajimatakahito probingthemutationallandscapeofthesarscov2spikeproteinviaquantummechanicalmodelingofcrystallographicstructures
AT johnsonwelkin probingthemutationallandscapeofthesarscov2spikeproteinviaquantummechanicalmodelingofcrystallographicstructures
AT farzanmichael probingthemutationallandscapeofthesarscov2spikeproteinviaquantummechanicalmodelingofcrystallographicstructures
AT momenibabak probingthemutationallandscapeofthesarscov2spikeproteinviaquantummechanicalmodelingofcrystallographicstructures