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Screening of Common Herbal Medicines as Promising Direct Inhibitors of Sars-Cov-2 in Silico

TLDR
Coumarylquinic acid and stigmasterol have powerful binding in silico, further in vitro studies include using viral infected human lung cells and testing above compounds ability for inhibiting viral entry and replication should be proceed to confirm the study results.
Abstract
Background: Molecular docking has been used recently in pharma industry for drug designing, it’s a powerful tool to find ligand-substrate interactions at molecules level. Since urgent need to develop anti-viral drug that target new coronavirus main proteins, in silico docking has been used to achieve this purpose. Materials and Methods: Thirteen herbs are known for their antioxidants and antiviral properties have been selected to investigate their abilities in inhibiting SARS-COV2 spike protein and main protease Mpro. pdb files for RBD (Receptor Binding Domain) region of spike protein and for Mpro and mol2 files for all herbs understudy were uploaded for swiss dock online server, the docking results were analyzed using chimera software. Full fitness energy and hydrogens bonds interactions were considered for docking evaluation. Pharma kinetic properties for compounds have good binding results were evaluated through AMES and ADMET tests. Original Research Article AL-Jassani et al.; ARRB, 35(8): 53-67, 2020; Article no.ARRB.59980 54 Results: All compounds showed negative full fitness energy that means they are able to complex with both SARS-COV2 spike protein and main protease, however some of the herbs form very powerful hydrogen bonding with the RBD site of the spike protein and the catalytic site of Mpro such as coumarylquinic acid, while stigmasterol has strong binding with the spike protein only. Both compounds appear to be safe drugs for human according to AMES test results. Conclusion: Coumarylquinic acid and stigmasterol have powerful binding in silico, further in vitro studies include using viral infected human lung cells and testing above compounds ability for inhibiting viral entry and replication should be proceed to confirm the study results.

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Methodology-centered review of molecular modeling, simulation, and prediction of SARS-CoV-2

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

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Molecular docking studies of some selected gallic acid derivatives against five non-structural proteins of novel coronavirus.

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In Silico molecular docking and dynamic analysis of natural compounds against major non-structural proteins of SARS-COV-2.

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Novel Molecules derived from 3-O-(6-galloylglucoside) inhibit Main Protease of SARS-CoV 2 In Silico.

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References
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Journal ArticleDOI

UCSF Chimera--a visualization system for exploratory research and analysis.

TL;DR: Two unusual extensions are presented: Multiscale, which adds the ability to visualize large‐scale molecular assemblies such as viral coats, and Collaboratory, which allows researchers to share a Chimera session interactively despite being at separate locales.
Journal ArticleDOI

A pneumonia outbreak associated with a new coronavirus of probable bat origin

TL;DR: Identification and characterization of a new coronavirus (2019-nCoV), which caused an epidemic of acute respiratory syndrome in humans in Wuhan, China, and it is shown that this virus belongs to the species of SARSr-CoV, indicates that the virus is related to a bat coronav virus.
Journal ArticleDOI

Evolution of the novel coronavirus from the ongoing Wuhan outbreak and modeling of its spike protein for risk of human transmission

TL;DR: Key Laboratory of Molecular Virology and Immunology, Institut Pasteur of Shanghai, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Shanghai 200031, China; Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Chinese academy of sciences, Shanghai200032, China.
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SwissDock, a protein-small molecule docking web service based on EADock DSS

TL;DR: SwissDock, a web server dedicated to the docking of small molecules on target proteins, is presented, based on the EADock DSS engine, combined with setup scripts for curating common problems and for preparing both the target protein and the ligand input files.
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