In silico analysis of RNA-dependent RNA polymerase of the SARS-CoV-2 and therapeutic potential of existing antiviral drugs

Mondal, Sukumar; Mukhoty, Samyabrata; Kundu, Himangsu; Ghosh, Subhajit; Sen, Madhab Kumar; Das, Suvankar; Brogi, Simone

doi:10.1016/j.compbiomed.2021.104591

Cited by 12 publications

(14 citation statements)

References 66 publications

(66 reference statements)

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“…Another extensive screening based on ADMET, docking, and MD simulations was implemented by Ghazwani et al, which covers 13840 compounds . Singh et al, Mondal et al, Begum et al, and Pokhrel et al evaluated the potency of thousands of existing drugs via docking and MD simulations. Tens of fungal secondary metabolites were docked to RdRp by Ebrahimi et al, and MD simulations were performed on the top five compounds .…”

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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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.

View full text Add to dashboard Cite

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“…Ultimately, MODELLER builds the structural models based on the templates selected. The interaction energy between the two given macromolecules of interest is calculated by a hierarchical fast Fourier transform (FFT)-based docking program ( Mondal et al, 2021 ) .…”

Section: Methodsmentioning

confidence: 99%

Virtual screening and docking analysis of novel ligands for selective enhancement of tea (Camellia sinensis) flavonoids

et al. 2022

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“…Protein–protein docking, using the RDB of viral spike protein as the ligand and h ACE2 as the receptor, was conducted employing the HDOCK webserver ( http://hdock.phys.hust.edu.cn/ accessed on May 12, 2022) [ 18 , 19 ]. The server performed protein–protein and protein-DNA/RNA docking automatically and can predict interactions by employing a hybrid algorithm of template-based and template-free docking.…”

Section: Methodsmentioning

confidence: 99%

Butein as a potential binder of human ACE2 receptor for interfering with SARS-CoV-2 entry: a computer-aided analysis

et al. 2022

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Natural products have been included in our dietary supplements and have been shown to have numerous therapeutic properties. With the looming danger of many zoonotic agents and novel emerging pathogens mainly of viral origin, many researchers are launching various clinical trials, testing these compounds for their antiviral activity. The present work deals with some of the available natural compounds from the literature that have demonstrated activity in counteracting pathogen infections. Accordingly, we screened, using in silico methods, this subset of natural compounds for searching potential drug candidates able to interfere in the recognition of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and its target human angiotensin-converting enzyme 2 ( h ACE2) receptor, leading to the viral entry. Disrupting that recognition is crucial for slowing down the entrance of viral particles into host cells. The selected group of natural products was examined, and their interaction profiles against the host cell target protein ACE2 were studied at the atomic level. Based on different computer-based procedures including molecular docking, physicochemical property evaluation, and molecular dynamics, butein was identified as a potential hit molecule able to bind the h ACE2 receptor. The results indicate that herbal compounds can be effective for providing possible therapeutics for treating and managing coronavirus disease 2019 (COVID-19) infection. Graphical abstract

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In silico analysis of RNA-dependent RNA polymerase of the SARS-CoV-2 and therapeutic potential of existing antiviral drugs

Cited by 12 publications

References 66 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

Virtual screening and docking analysis of novel ligands for selective enhancement of tea (Camellia sinensis) flavonoids

Butein as a potential binder of human ACE2 receptor for interfering with SARS-CoV-2 entry: a computer-aided analysis

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