Pre-Existing Oxidative Stress Creates a Docking-Ready Conformation of the SARS-CoV-2 Receptor-Binding Domain

Fossum, Carl J.; Laatsch, Bethany F.; Lowater, Harrison R.; Narkiewicz-Jodko, Alex; Lonzarich, Leo; Hati, Sanchita; Bhattacharyya, Sudeep

doi:10.1021/acsbiomedchemau.1c00040

Cited by 12 publications

(36 citation statements)

References 50 publications

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“…MD simulations and MM/PBSA calculations revealed that the formation of disulfide bonds, prevalent during oxidative stress, created a conformation more ready to bind to the receptor, which offered future clues for alternate therapeutic possibilities. 497 Similar work was also performed by Ghasemitarei et al 498 One interesting study performed MM/PBSA calculations to reveal the binding affinities of SARS-CoV-2 S protein to the ACE2s from different species. 499 , 500 This study showed that chimpanzees’ binding affinity was even higher than humans, cats, pangolin, dogs, and monkeys, and chimpanzees had a similar affinity to humans, which suggested some mammals were also vulnerable to SARS-CoV-2.…”

Section: Methods and Approachesmentioning

confidence: 72%

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Gao¹,

Wang²,

Chen³

et al. 2022

Chem. Rev.

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Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus–host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein–protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

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Section: Methods and Approachesmentioning

confidence: 72%

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Gao¹,

Wang²,

Chen³

et al. 2022

Chem. Rev.

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show abstract

“…Therefore, the simulation data was analyzed to examine any alteration in the inter-residue interaction at the interface of the RBD and PD domain. Earlier MD simulation studies [ 17 , 18 ] reported several key residues at the interface. In particular, a recent study by Fossum et al [ 17 ] identified three distinct zones in WT (Table 3 ), where interacting residue clusters were observed to be essential in providing a tighter binding between the RBM to the ACE2.…”

Section: Resultsmentioning

confidence: 99%

“…Earlier MD simulation studies [ 17 , 18 ] reported several key residues at the interface. In particular, a recent study by Fossum et al [ 17 ] identified three distinct zones in WT (Table 3 ), where interacting residue clusters were observed to be essential in providing a tighter binding between the RBM to the ACE2. As shown in Table 3 , the left zone consists of two aromatic–aromatic interactions, namely, Y489(OH)···F28(N) and Y489(OH)···Y83(OH).…”

Section: Resultsmentioning

confidence: 99%

“…The channel is surrounded by ridges that contain loops, helices, and a fraction of a β-sheet. At the surface of the ACE2, ridges are consisting of two large α-helices containing Ser19 through Tyr83 [ 17 ] that serves as a binding motif for the concave RBD of SARS-CoV-2. The two α-helices near the N-terminal (residues 19–54) act as shaft allowing the concave surface of the SARS-CoV-2 to anchor on it.…”

Section: Introductionmentioning

confidence: 99%

“…The two α-helices near the N-terminal (residues 19–54) act as shaft allowing the concave surface of the SARS-CoV-2 to anchor on it. [ 17 , 18 ]…”

Section: Introductionmentioning

confidence: 99%

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Evolution of Stronger SARS-CoV-2 Variants as Revealed Through the Lens of Molecular Dynamics Simulations

et al. 2022

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Using molecular dynamics simulations, the protein–protein interactions of the receptor-binding domain of the wild-type and seven variants of the severe acute respiratory syndrome coronavirus 2 spike protein and the peptidase domain of human angiotensin-converting enzyme 2 were investigated. These variants are alpha, beta, gamma, delta, eta, kappa, and omicron. Using 100 ns simulation data, the residue interaction networks at the protein–protein interface were identified. Also, the impact of mutations on essential protein dynamics, backbone flexibility, and interaction energy of the simulated protein–protein complexes were studied. The protein–protein interface for the wild-type, delta, and omicron variants contained several stronger interactions, while the alpha, beta, gamma, eta, and kappa variants exhibited an opposite scenario as evident from the analysis of the inter-residue interaction distances and pair-wise interaction energies. The study reveals that two distinct residue networks at the central and right contact regions forge stronger binding affinity between the protein partners. The study provides a molecular-level insight into how enhanced transmissibility and infectivity by delta and omicron variants are most likely tied to a handful of interacting residues at the binding interface, which could potentially be utilized for future antibody constructs and structure-based antiviral drug design. Supplementary Information The online version contains supplementary material available at 10.1007/s10930-022-10065-6.

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High-performance computing in undergraduate education at primarily undergraduate institutions in Wisconsin: Progress, challenges, and opportunities

Hebert,

Hratisch,

Gomes

et al. 2024

Educ Inf Technol

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Pre-Existing Oxidative Stress Creates a Docking-Ready Conformation of the SARS-CoV-2 Receptor-Binding Domain

Cited by 12 publications

References 50 publications

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Evolution of Stronger SARS-CoV-2 Variants as Revealed Through the Lens of Molecular Dynamics Simulations

High-performance computing in undergraduate education at primarily undergraduate institutions in Wisconsin: Progress, challenges, and opportunities

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