Single-molecule force stability of the SARS-CoV-2–ACE2 interface in variants-of-concern

Bauer, Magnus S.; Gruber, Sophia; Hausch, Adina; Melo, Marcelo C. R.; Gomes, Priscila S. F. C.; Nicolaus, Thomas; Milles, Lukas F.; Gaub, Hermann E.; Bernardi, Rafael C.; Lipfert, Jan

doi:10.1038/s41565-023-01536-7

Cited by 7 publications

(5 citation statements)

References 91 publications

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“…Lastly, leveraging a technique developed by our group we employed generalized-correlation-based Dynamic Network Analysis 45 to derive relative binding strengths. 51 The results, displayed in Fig. 2F and Fig.…”

Section: Resultsmentioning

confidence: 92%

Integrating Dynamic Network Analysis with AI for Enhanced Epitope Prediction in PD-L1:Affibody Interactions

Gomes,

Yang,

Vanella

et al. 2024

Preprint

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Understanding binding epitopes involved in protein-protein interactions and accurately determining their structure is a long standing goal with broad applicability in industry and biomedicine. Although various experimental methods for binding epitope determination exist, these approaches are typically low throughput and cost intensive. Computational methods have potential to accelerate epitope predictions, however, recently developed artificial intelligence (AI)-based methods frequently fail to predict epitopes of synthetic binding domains with few natural homologs. Here we have developed an integrated method employing generalized-correlation-based dynamic network analysis on multiple molecular dynamics (MD) trajectories, initiated from AlphaFold2 Multimer structures, to unravel the structure and binding epitope of the therapeutic PD-L1:Affibody complex. Both AlphaFold2 and conventional molecular dynamics trajectory analysis alone each proved ineffectual in differentiating between two putative binding models referred to as parallel and perpendicular. However, our integrated approach based on dynamic network analysis showed that the perpendicular mode was significantly more stable. These predictions were validated using a suite of experimental epitope mapping protocols including cross linking mass spectrometry and next-generation sequencing-based deep mutational scanning. Our research highlights the potential of deploying dynamic network analysis to refine AI-based structure predictions for precise predictions of protein-protein interaction interfaces.

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Section: Resultsmentioning

confidence: 92%

Integrating Dynamic Network Analysis with AI for Enhanced Epitope Prediction in PD-L1:Affibody Interactions

Gomes,

Yang,

Vanella

et al. 2024

Preprint

Self Cite

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“…For SARS-CoV-2, which may experience mechanical force during human sneezing and coughing, this technique mimics the external force from the dynamic airway on the protein during measurement. Thus, SMFS manipulation on the spike protein/RBD-ACE2 complex is physiologically relevant and has been studied [39]. For example, several groups have used SMFS to study the binding strength between the RBD and ACE2, especially for the various viral variants [40].…”

Section: Resultsmentioning

confidence: 99%

Molecular Mechanism of Interaction between DNA Aptamer and Receptor-Binding Domain of Severe Acute Respiratory Syndrome Coronavirus 2 Variants Revealed by Steered Molecular Dynamics Simulations

Ding,

Xu,

Zheng

et al. 2024

Molecules

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The ongoing SARS-CoV-2 pandemic has underscored the urgent need for versatile and rapidly deployable antiviral strategies. While vaccines have been pivotal in controlling the spread of the virus, the emergence of new variants continues to pose significant challenges to global health. Here, our study focuses on a novel approach to antiviral therapy using DNA aptamers, short oligonucleotides with high specificity and affinity for their targets, as potential inhibitors against the spike protein of SARS-CoV-2 variants Omicron and JN.1. Our research utilizes steered molecular dynamics (SMD) simulations to elucidate the binding mechanisms of a specifically designed DNA aptamer, AM032-4, to the receptor-binding domain (RBD) of the aforementioned variants. The simulations reveal detailed molecular insights into the aptamer–RBD interaction, demonstrating the aptamer’s potential to maintain effective binding in the face of rapid viral evolution. Our work not only demonstrates the dynamic interaction between aptamer–RBD for possible antiviral therapy but also introduces a computational method to study aptamer–protein interactions.

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“…The quantification of morphological changes in the receptor binding motif (RBM) during adsorption is a crucial step to determining the difference in function of the protein due to structural deformation. Figure shows the relationship between the perpendicular and parallel radius of gyration ( R g⊥ and R g∥ , respectively) of the RBM-inanimate (for both groups, as defined in Tables S7 and S8) and RBM-biological (both groups and the ACE2) and allows us a direct comparison among them for each VoC. − The interfaces with the PBLs are roughly within the semiflexible polymer regime ( ⟨ R g ⊥ / R g ∥ ⟩ 2 < 0.32 ). , In contrast, the biological interface RBM-ACE2 shows globular behavior. Although both hydrophobic and hydrophilic surfaces are in the same flexibility regime, we observe a difference in R g∥ between group 1 and group 2, due to the initial conformation of the residues in group 2, which are slightly more elongated (see Figure c,f for initial structures between both groups).…”

Section: Resultsmentioning

confidence: 99%

Adsorption-Driven Deformation and Footprints of the RBD Proteins in SARS-CoV-2 Variants on Biological and Inanimate Surfaces

Bosch,

Guzman,

Pérez

2024

J. Chem. Inf. Model.

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Respiratory viruses, carried through airborne microdroplets, frequently adhere to surfaces, including plastics and metals. However, our understanding of the interactions between viruses and materials remains limited, particularly in scenarios involving polarizable surfaces. Here, we investigate the role of the receptor-binding domain (RBD) of the spike protein mutations on the adsorption of SARS-CoV-2 to hydrophobic and hydrophilic surfaces employing molecular simulations. To contextualize our findings, we contrast the interactions on inanimate surfaces with those on native biological interfaces, specifically the angiotensinconverting enzyme 2. Notably, we identify a 2-fold increase in structural deformations for the protein's receptor binding motif (RBM) onto inanimate surfaces, indicative of enhanced shock-absorbing mechanisms. Furthermore, the distribution of adsorbed amino acids (landing footprints) on the inanimate surface reveals a distinct regional asymmetry relative to the biological interface, with roughly half of the adsorbed amino acids arranged in opposite sites. In spite of the H-bonds formed at the hydrophilic substrate, the simulations consistently show a higher number of contacts and interfacial area with the hydrophobic surface, where the wild-type RBD adsorbs more strongly than the Delta or Omicron RBDs. In contrast, the adsorption of Delta and Omicron to hydrophilic surfaces was characterized by a distinctive hopping-pattern. The novel shock-absorbing mechanisms identified in the virus adsorption on inanimate surfaces show the embedded high-deformation capacity of the RBD without losing its secondary structure, which could lead to current experimental strategies in the design of virucidal surfaces.

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Single-molecule force stability of the SARS-CoV-2–ACE2 interface in variants-of-concern

Cited by 7 publications

References 91 publications

Integrating Dynamic Network Analysis with AI for Enhanced Epitope Prediction in PD-L1:Affibody Interactions

Integrating Dynamic Network Analysis with AI for Enhanced Epitope Prediction in PD-L1:Affibody Interactions

Molecular Mechanism of Interaction between DNA Aptamer and Receptor-Binding Domain of Severe Acute Respiratory Syndrome Coronavirus 2 Variants Revealed by Steered Molecular Dynamics Simulations

Adsorption-Driven Deformation and Footprints of the RBD Proteins in SARS-CoV-2 Variants on Biological and Inanimate Surfaces

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