Computational designing of a peptide that potentially blocks the entry of SARS-CoV, SARS-CoV-2 and MERS-CoV

Priya, Vishnu; Rath, Satish; Abraham, Parvin

doi:10.1371/journal.pone.0251913

Cited by 8 publications

(4 citation statements)

References 45 publications

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“…In addition, P18 and P20 had higher binding energy than DIENLIKSQ when employing the same HawkDock server ( Padhi et al, 2021 ). The computationally designed peptide APASMFLGKGDHEILM made no interactions with the active site when docked using the same HPEPDOCK server that we used for our top four peptides ( Priya et al, 2021 ). Another peptide modeling and screening study suggested that AVP0671 can bind to the RBD, albeit not at the active site, and the HDOCK scores were not reported.…”

Section: Resultsmentioning

confidence: 99%

“…Several previous studies have suggested antiviral effects of small molecules and peptides against SARS-CoV-2 through binding to the RBD. These studies identified molecules that, although they were predicted to bind to the RBD, did not interact directly with the RBD active site ( Rathod et al, 2020 ; Padhi et al, 2021 ; Priya et al, 2021 ). In contrast, all of the peptides we identified were predicted to bind directly to the RBD active site.…”

Section: Introductionmentioning

confidence: 99%

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Molecular Docking and Dynamics Studies to Explore Effective Inhibitory Peptides Against the Spike Receptor Binding Domain of SARS-CoV-2

Biswas

Mahmud

Mita

et al. 2022

Front. Mol. Biosci.

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The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a pandemic due to the high transmission and mortality rate of this virus. The world health and economic sectors have been severely affected by this deadly virus, exacerbated by the lack of sufficient efficient vaccines. The design of effective drug candidates and their rapid development is necessary to combat this virus. In this study, we selected 23 antimicrobial peptides from the literature and predicted their structure using PEP-FOLD 3.5. In addition, we docked them to the SARS-CoV-2 spike protein receptor-binding domain (RBD) to study their capability to inhibit the RBD, which plays a significant role in virus binding, fusion and entry into the host cell. We used several docking programs including HDOCK, HPEPDOCK, ClusPro, and HawkDock to calculate the binding energy of the protein-peptide complexes. We identified four peptides with high binding free energy and docking scores. The docking results were further verified by molecular dynamics (MD) simulations to characterize the protein-peptide complexes in terms of their root-mean-square fluctuation (RMSF), root-mean-square deviation (RMSD), radius of gyration (Rg), solvent-accessible surface area (SASA), and hydrogen bond formation. Allergenicity and toxicity predictions suggested that the peptides we identified were non-allergenic and non-toxic. This study suggests that these four antimicrobial peptides could inhibit the RBD of SARS-CoV-2. Future in vitro and in vivo studies are necessary to confirm this.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Molecular Docking and Dynamics Studies to Explore Effective Inhibitory Peptides Against the Spike Receptor Binding Domain of SARS-CoV-2

Biswas

Mahmud

Mita

et al. 2022

Front. Mol. Biosci.

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“…One study predicted the affinities of the peptide analogues Seq12, Seq12m, and Seq13m to S protein through molecular docking, MD simulation, and MM-PB/GBSA calculations . Other docking and MD studies of peptides to S protein include refs and − . In addition, potency of peptides to other targets was also anticipated.…”

Section: Methods and Approachesmentioning

confidence: 99%

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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“…In the context of viral infection examples such as the FDA-approved peptide Enfurvirtide [16] and further research (reviewed in [17,18]) illustrate the use of peptides as potential agents to block PPIs. In fact, a number of recent publications has shown promising results on the use of peptides to blocks the entrance of SARS-CoV-2 virus using peptides derived from native element of the interaction humanACE2 and SARS-CoV-2 spike [19][20][21] including designed peptides targeting of the heptad repeat 1 region [22], the RBD domain [23][24][25], with validation in cell-cultures [26,27] and tissues [28]. While these approaches rely on the sequence diversification of existing native elements, ours complements these efforts by providing novel sequences (next).…”

Section: Introductionmentioning

confidence: 99%

A Collection of Designed Peptides to Target SARS-CoV-2 Spike RBD—ACE2 Interaction

Fernández-Fuentes

Molina

Oliva

2021

IJMS

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The angiotensin-converting enzyme 2 (ACE2) is the receptor used by SARS-CoV and SARS-CoV-2 coronaviruses to attach to cells via the receptor-binding domain (RBD) of their viral spike protein. Since the start of the COVID-19 pandemic, several structures of protein complexes involving ACE2 and RBD as well as monoclonal antibodies and nanobodies have become available. We have leveraged the structural data to design peptides to target the interaction between the RBD of SARS-CoV-2 and ACE2 and SARS-CoV and ACE2, as contrasting exemplar, as well as the dimerization surface of ACE2 monomers. The peptides were modelled using our original method: PiPreD that uses native elements of the interaction between the targeted protein and cognate partner(s) that are subsequently included in the designed peptides. These peptides recapitulate stretches of residues present in the native interface plus novel and highly diverse conformations surrogating key interactions at the interface. To facilitate the access to this information we have created a freely available and dedicated web-based repository, PepI-Covid19 database, providing convenient access to this wealth of information to the scientific community with the view of maximizing its potential impact in the development of novel therapeutic and diagnostic agents.

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Computational designing of a peptide that potentially blocks the entry of SARS-CoV, SARS-CoV-2 and MERS-CoV

Cited by 8 publications

References 45 publications

Molecular Docking and Dynamics Studies to Explore Effective Inhibitory Peptides Against the Spike Receptor Binding Domain of SARS-CoV-2

Molecular Docking and Dynamics Studies to Explore Effective Inhibitory Peptides Against the Spike Receptor Binding Domain of SARS-CoV-2

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

A Collection of Designed Peptides to Target SARS-CoV-2 Spike RBD—ACE2 Interaction

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