scholarly journals The SARS-CoV-2 Exerts a Distinctive Strategy for Interacting with the ACE2 Human Receptor

Viruses ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 497 ◽  
Author(s):  
Esther S. Brielle ◽  
Dina Schneidman-Duhovny ◽  
Michal Linial
Keyword(s):  
Cell Receptor ◽  
Host Recognition ◽  
Interface Residue ◽  
Binding Affinities ◽  
Binding Interface ◽  
Residue Contacts ◽  
High Infection ◽  
Dynamics Simulations ◽  
Insight Into ◽  
Human Receptor

The COVID-19 disease has plagued over 200 countries with over three million cases and has resulted in over 200,000 deaths within 3 months. To gain insight into the high infection rate of the SARS-CoV-2 virus, we compare the interaction between the human ACE2 receptor and the SARS-CoV-2 spike protein with that of other pathogenic coronaviruses using molecular dynamics simulations. SARS-CoV, SARS-CoV-2, and HCoV-NL63 recognize ACE2 as the natural receptor but present a distinct binding interface to ACE2 and a different network of residue–residue contacts. SARS-CoV and SARS-CoV-2 have comparable binding affinities achieved by balancing energetics and dynamics. The SARS-CoV-2–ACE2 complex contains a higher number of contacts, a larger interface area, and decreased interface residue fluctuations relative to the SARS-CoV–ACE2 complex. These findings expose an exceptional evolutionary exploration exerted by coronaviruses toward host recognition. We postulate that the versatility of cell receptor binding strategies has immediate implications for therapeutic strategies.

scholarly journals The SARS-CoV-2 exerts a distinctive strategy for interacting with the ACE2 human receptor

2020 ◽  
Author(s):  
Esther S. Brielle ◽  
Dina Schneidman-Duhovny ◽  
Michal Linial
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Cell Receptor ◽  
Host Recognition ◽  
Interface Residue ◽  
Binding Affinities ◽  
Temporal Dimension ◽  
Binding Interface ◽  
Residue Contacts ◽  
Dynamics Simulations

AbstractThe COVID-19 disease has plagued over 110 countries and has resulted in over 4,000 deaths within 10 weeks. We compare the interaction between the human ACE2 receptor and the SARS-CoV-2 spike protein with that of other pathogenic coronaviruses using molecular dynamics simulations. SARS-CoV, SARS-CoV-2, and HCoV-NL63 recognize ACE2 as the natural receptor but present a distinct binding interface to ACE2 and a different network of residue-residue contacts. SARS-CoV and SARS-CoV-2 have comparable binding affinities achieved by balancing energetics and dynamics. The SARS-CoV-2–ACE2 complex contains a higher number of contacts, a larger interface area, and decreased interface residue fluctuations relative to SARS-CoV. These findings expose an exceptional evolutionary exploration exerted by coronaviruses toward host recognition. We postulate that the versatility of cell receptor binding strategies has immediate implications on therapeutic strategies.One Sentence SummaryMolecular dynamics simulations reveal a temporal dimension of coronaviruses interactions with the host receptor.

scholarly journals Mechanistic Insights into the Effects of Key Mutations on SARS-CoV-2 RBD-ACE2 Binding

2021 ◽  
Author(s):  
Abhishek Aggarwal ◽  
Supriyo Naskar ◽  
Nikhil Maroli ◽  
Biswajit Gorai ◽  
Narendra M Dixit ◽  
...  
Keyword(s):  
Structural Changes ◽  
Underlying Mechanism ◽  
Free Energy Calculations ◽  
Target Cells ◽  
Original Strain ◽  
Binding Affinities ◽  
Receptor Binding Domain ◽  
Wild Type ◽  
Dynamics Simulations ◽  
Insight Into

Some recent SARS-CoV-2 variants appear to have increased transmissibility than the original strain. An underlying mechanism could be the improved ability of the variants to bind receptors on target cells and infect them. In this study, we provide atomic-level insight into the binding of the receptor binding domain (RBD) of the wild-type SARS-CoV-2 spike protein and its single (N501Y), double (E484Q, L452R) and triple (N501Y, E484Q, L452R) mutated variants to the human ACE2 receptor. Using extensive all-atom molecular dynamics simulations and advanced free energy calculations, we estimate the associated binding affinities and binding hotspots. We observe significant secondary structural changes in the RBD of the mutants, which lead to different binding affinities. We find higher binding affinities of the double (E484Q, L452R) and triple (N501Y, E484Q, L452R) mutated variants than the wild type and the N501Y variant, which could contribute to the higher transmissibility of recent variants containing these mutations.

scholarly journals Decomposition of the SARS-CoV-2-ACE2 interface reveals a common trend among emerging viral variants

2021 ◽  
Author(s):  
Eileen Socher ◽  
Marcus Conrad ◽  
Lukas Heger ◽  
Friedrich Paulsen ◽  
Heinrich Sticht ◽  
...  
Keyword(s):  
Amino Acid ◽  
Host Cell ◽  
Cell Receptor ◽  
Cell Interaction ◽  
Therapeutic Interventions ◽  
Host Cell Receptor ◽  
Common Trend ◽  
Binding Interface ◽  
Dynamics Simulations ◽  
Viral Surface

New viral variants of the SARS-CoV-2 virus show enhanced infectivity compared to wild type, resulting in an altered pandemic situation in affected areas. These variants are the B.1.1.7 (United Kingdom), B.1.1.7 with the additional E484K mutation, the B.1.351 variant (South Africa) and the P.1 variant (Brazil). Understanding the binding modalities between these viral variants and the host cell receptor ACE2 allows depicting changes, but also common motifs of virus-host cell interaction. The trimeric spike protein expressed at the viral surface contains the receptor-binding domain (RBD) that forms the molecular interface with ACE2. All the above-mentioned variants carry between one and three amino acid exchanges within the interface-forming region of the RBD, thereby altering the binding interface with ACE2. Using molecular dynamics simulations and decomposition of the interaction energies between the RBD and ACE2, we identified phenylalanine 486, glutamine 498, threonine 500 and tyrosine 505 as important interface-forming residues across viral variants. We also suggest a reduced binding energy between RBD and ACE2 in viral variants with higher infectivity, attributed to residue-specific differences in electrostatic interaction energy. Importantly, individual amino acid exchanges not only influence the affected position, but also alter the conformation of surrounding residues and affect their interaction potential as well. We demonstrate how computational methods can help to identify changed as well as common motifs across viral variants. These identified motifs might play a crucial role, in the strategical development of therapeutic interventions against the fast mutating SARS-CoV-2 virus.

scholarly journals Identifying key determinants and dynamics of SARS-CoV-2/ACE2 tight interaction

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257905
Author(s):  
Van A. Ngo ◽  
Ramesh K. Jha
Keyword(s):  
Receptor Binding ◽  
Dissociation Rate ◽  
Receptor Protein ◽  
Terminal Part ◽  
Angiotensin Converting Enzyme 2 ◽  
Binding Interface ◽  
Global Pandemic ◽  
Key Residues ◽  
Insight Into ◽  
Human Receptor

SARS-CoV-2 virus, the causative agent of Covid-19, has fired up a global pandemic. The virus interacts with the human receptor angiotensin-converting enzyme 2 (ACE2) for an invasion via receptor binding domain (RBD) on its spike protein. To provide a deeper understanding of this interaction, we performed microsecond simulations of the RBD-ACE2 complex for SARS-CoV-2 and compared it with the closely related SARS-CoV discovered in 2003. We show residues in the RBD of SARS-CoV-2 that were mutated from SARS-CoV, collectively help make the RBD anchor much stronger to the N-terminal part of ACE2 than the corresponding residues on RBD of SARS-CoV. This would result in a reduced dissociation rate of SARS-CoV-2 from human receptor protein compared to SARS-CoV. The phenomenon was consistently observed in simulations beyond 500 ns and was reproducible across different force fields. Altogether, our study adds more insight into the critical dynamics of the key residues at the virus spike and human receptor binding interface and potentially aids the development of diagnostics and therapeutics to combat the pandemic efficiently.

scholarly journals Reliable in silico ranking of engineered therapeutic TCR binding affinities using MMPBSA and MMGBSA calculations.

2021 ◽  
Author(s):  
Marc W. Van der Kamp ◽  
Rory M. Crean ◽  
David K. Cole ◽  
Christopher R. Pudney
Keyword(s):  
Protein Design ◽  
In Silico ◽  
Single Point ◽  
Computational Cost ◽  
Human Leukocyte ◽  
Md Simulations ◽  
Cell Receptor ◽  
Scoring Functions ◽  
Binding Affinities ◽  
Binding Interface

Accurate and efficient in silico ranking of protein-protein binding affinities is useful for protein design with applications in biological therapeutics. One popular approach to rank binding affinities is to apply the molecular mechanics Poisson Boltzmann/generalized Born surface area (MMPB/GBSA) method to molecular dynamics trajectories. This provides a compromise between rapid but approximate scoring functions of single structures and more sophisticated methods such as free energy perturbation. Optimal MMPB/GBSA parameters tend to be system specific. Here, we identify protocols that enable reliable evaluation of the effect of mutations in a T-cell receptor (TCR) in complex with its natural target, the peptide-human leukocyte antigen (pHLA). The development of affinity-enhanced engineered TCRs towards a specific pHLA is of great interest in the field of immunotherapy. Our study highlights the importance of using a higher than default internal dielectric constant, especially in the case of charge changing mutations. Including explicit solvation and/or entropy corrections may deteriorate the ranking of single point variants due to the errors associated with these additions. For multi-point variants, however, these corrections were important for accurate ranking. We also demonstrate how potential outliers could be identified in advance by analyzing changes in the hydrogen bonding networks at the binding interface. Finally, using bootstrapping we show that as few as 5-10 replicas of short (4 ns) MD simulations may be sufficient for reproducible and accurate ranking of candidate TCR variants. Our work demonstrates that reliably ranking TCR variant binding affinities can be achieved at moderate computational cost. The protocols developed here can be applied towards in silico screening during the optimization of therapeutic TCRs, potentially reducing both the cost and time taken for biologic development.

scholarly journals Insight into the origin of SARS-CoV-2 through structural analysis of receptor recognition: a molecular simulation study

RSC Advances ◽  
2021 ◽  
Vol 11 (15) ◽  
pp. 8718-8729
Author(s):  
Jixue Sun ◽  
Meijiang Liu ◽  
Na Yang
Keyword(s):  
Molecular Dynamics ◽  
Structural Analysis ◽  
Molecular Dynamics Simulations ◽  
Molecular Simulation ◽  
Simulation Study ◽  
Receptor Recognition ◽  
Dynamics Simulations ◽  
Insight Into

The origin of SARS-CoV-2 through structural analysis of receptor recognition was investigated by molecular dynamics simulations.

scholarly journals Computational Design of Radical Recognition Assay with the Possible Application of Cyclopropyl Vinyl Sulfides as Tunable Sensors

2021 ◽  
Vol 22 (14) ◽  
pp. 7637
Author(s):  
Liliya T. Sahharova ◽  
Evgeniy G. Gordeev ◽  
Dmitry B. Eremin ◽  
Valentine P. Ananikov
Keyword(s):  
Uv Light ◽  
Computational Design ◽  
Energy Profiles ◽  
Vinyl Sulfides ◽  
Tunable Sensors ◽  
Radical Generation ◽  
Metal Catalyzed ◽  
Dynamics Simulations ◽  
Simulations And Modeling ◽  
Insight Into

The processes involving the capture of free radicals were explored by performing DFT molecular dynamics simulations and modeling of reaction energy profiles. We describe the idea of a radical recognition assay, where not only the presence of a radical but also the nature/reactivity of a radical may be assessed. The idea is to utilize a set of radical-sensitive molecules as tunable sensors, followed by insight into the studied radical species based on the observed reactivity/selectivity. We utilize this approach for selective recognition of common radicals—alkyl, phenyl, and iodine. By matching quantum chemical calculations with experimental data, we show that components of a system react differently with the studied radicals. Possible radical generation processes were studied involving model reactions under UV light and metal-catalyzed conditions.

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