Computational Prediction of Mutational Effects on the SARS-CoV-2 Binding by Relative Free Energy Calculations

Zou, Junjie; Yin, Jie; Fang, Lei; Yang, Mingjun; Wang, Tianyuan; Wu, Weikun; Zhang, Peiyu

doi:10.26434/chemrxiv.11902623.v1

Cited by 16 publications

(15 citation statements)

References 29 publications

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“…Almost all high-importance residues were mutated in SARS-CoV-2 compared to SARS-CoV. Six of the seven mutations identified in our ML approaches were also highlighted in previous studies: Val404/Lys417, Arg426/ Asn439, Tyr442/Leu455, Leu443/Phe456, Tyr484/Gln498, and Thr487/Asn501, 13,14,23,24 demonstrating the ability of our approach to replicate human insight.…”

supporting

confidence: 77%

Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2

Pavlova

Zhang

Acharya

et al. 2021

J. Phys. Chem. Lett.

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SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Herein, we have used molecular dynamics (MD) simulations, machine learning (ML), and free-energy perturbation (FEP) calculations to elucidate the differences in binding by the two viruses. Although only subtle differences were observed from the initial MD simulations of the two RBD–ACE2 complexes, ML identified the individual residues with the most distinctive ACE2 interactions, many of which have been highlighted in previous experimental studies. FEP calculations quantified the corresponding differences in binding free energies to ACE2, and examination of MD trajectories provided structural explanations for these differences. Lastly, the energetics of emerging SARS-CoV-2 mutations were studied, showing that the affinity of the RBD for ACE2 is increased by N501Y and E484K mutations but is slightly decreased by K417N.

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supporting

confidence: 77%

Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2

Pavlova

Zhang

Acharya

et al. 2021

J. Phys. Chem. Lett.

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“…The isolated RBD of the SARS-CoV-2 S protein binds ACE2 more strongly than that of SARS, but the complete S proteins bind with nearly the same affinity. 14,17,19,23,35 SARS-CoV-2 S is thought to occupy the active, open RBD state less often than in the SARS S, but is compensated by the greater affinity of the RBD for ACE2. 23 Since the RBD is largely obscured by the glycan shield in the closed state, 32 the shifted equilibrium allows the SARS-CoV-2 spike to spend less time in the vulnerable open conformation without sacrificing net affinity for ACE2.…”

Section: ■ Introductionmentioning

confidence: 99%

Free Energy Landscapes from SARS-CoV-2 Spike Glycoprotein Simulations Suggest that RBD Opening Can Be Modulated via Interactions in an Allosteric Pocket

et al. 2021

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The SARS-CoV-2 coronavirus is an enveloped, positive-sense single-stranded RNA virus that is responsible for the COVID-19 pandemic. The spike is a class I viral fusion glycoprotein that extends from the viral surface and is responsible for viral entry into the host cell and is the primary target of neutralizing antibodies. The receptor binding domain (RBD) of the spike samples multiple conformations in a compromise between evading immune recognition and searching for the host-cell surface receptor. Using atomistic simulations of the glycosylated wild-type spike in the closed and 1-up RBD conformations, we map the free energy landscape for RBD opening and identify interactions in an allosteric pocket that influence RBD dynamics. The results provide an explanation for experimental observation of increased antibody binding for a clinical variant with a substitution in this pocket. Our results also suggest the possibility of allosteric targeting of the RBD equilibrium to favor open states via binding of small molecules to the hinge pocket. In addition to potential value as experimental probes to quantify RBD conformational heterogeneity, small molecules that modulate the RBD equilibrium could help explore the relationship between RBD opening and S1 shedding.

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“…Several MD studies have revealed the molecular details of RBD-hACE2 interactions and identified the molecular traits responsible for the enhanced binding capacity of SARS-COV-2 with hACE2 than the SARS-COV-1 variant. 11,15,21,23,33 Binding of hACE2 with the SARS-CoV-2 S/RBD is largely driven by electrostatic interactions with a delicate network of H-bonds, hydrophobic contacts, - and cation- interactions. 36 Sequence variations between the RBMs of the two SARS variants mainly aggregate in the loop regions.…”

Section: Resultsmentioning

confidence: 99%

Unbinding of hACE2 and Inhibitors from the Receptor Binding Domain of SARS-CoV-2 Spike Protein

Mishra

Bandyopadhyay

2021

Preprint

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The first direful biomolecular event leading to COVID-19 disease is the SARS-CoV-2 virus surface spike (S) protein-mediated interaction with the human transmembrane protein, angiotensin-converting enzyme 2 (hACE2). Prevention of this interaction presents an attractive alternative to thwart SARS-CoV-2 replications. The development of monoclonal antibodies (mAbs) in the convalescent plasma treatment, nanobody, and designer peptides, which recognizes epitopes that overlap with hACE2 binding sites in the receptor-binding domain (RBD) of S protein (S/RBD) and thereby blocking the infection has been the center stage of therapeutic research. Here we report atomistic and reliable in silico structure-energetic features of the S/RBD interactions with hACE2 and its two inhibitors (convalescent mAb, B38, and an alpaca nanobody, Ty1). The discovered potential of mean forces exhibits free energy basin and barriers along the interaction pathways, providing sufficient molecular insights to design a B38 mutant and a Ty1-based peptide with higher binding capacity. While the mutated B38 forms a 60-fold deeper free energy minimum, the designer peptide (Ty1-based) constitutes 38 amino acids and is found to form a 100-fold deeper free energy minimum in the first binding basin than their wild-type variants in complex with S/RBD. Our strategy may help to design more efficacious biologics towards therapeutic intervention against the current raging pandemic.

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Computational Prediction of Mutational Effects on the SARS-CoV-2 Binding by Relative Free Energy Calculations

Cited by 16 publications

References 29 publications

Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2

Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2

Free Energy Landscapes from SARS-CoV-2 Spike Glycoprotein Simulations Suggest that RBD Opening Can Be Modulated via Interactions in an Allosteric Pocket

Unbinding of hACE2 and Inhibitors from the Receptor Binding Domain of SARS-CoV-2 Spike Protein

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