New α-Hydrazinophosphonic acid: Synthesis, characterization, DFT study and in silico prediction of its potential inhibition of SARS-CoV-2 main protease

The Severe Acute Respiratory Syndrome 2 (SARS-CoV-2) is an infectious virus that causes mild to severe life-threatening upper respiratory tract infection. The virus emerged in Wuhan, China in 2019, and later spread across the globe. Its genome has been completely sequenced and based on the genomic information, the virus possessed 3C-Like Main Protease (3CLpro), an essential multifunctional enzyme that plays a vital role in the replication and transcription of the virus by cleaving polyprotein at eleven various sites to produce different non-structural proteins. This makes the protein an important target for drug design and discovery. Herein, we analyzed the interaction between the 3CLpro and potential inhibitory compounds identified from the extracts of Zingiber offinale and Anacardium occidentale using in silico docking and Molecular Dynamics (MD) Simulation. The crystal structure of SARS-CoV-2 main protease in complex with 02J (5-Methylisoxazole-3-carboxylic acid) and PEJ (composite ligand) (PDB Code: 6LU7,2.16Å) retrieved from Protein Data Bank (PDB) and subject to structure optimization and energy minimization. A total of twenty-nine compounds were obtained from the extracts of Zingiber offinale and the leaves of Anacardium occidentale. These compounds were screened for physicochemical (Lipinski rule of five, Veber rule, and Egan filter), Pan-Assay Interference Structure (PAINS), and pharmacokinetic properties to determine the Pharmaceutical Active Ingredients (PAIs). Of the 29 compounds, only nineteen (19) possessed drug-likeness properties with efficient oral bioavailability and less toxicity. These compounds subjected to molecular docking analysis to determine their binding energies with the 3CLpro. The result of the analysis indicated that the free binding energies of the compounds ranged between ˗5.08 and -10.24kcal/mol, better than the binding energies of 02j (-4.10kcal/mol) and PJE (-5.07kcal.mol). Six compounds (CID_99615 = -10.24kcal/mol, CID_3981360 = 9.75kcal/mol, CID_9910474 = -9.14kcal/mol, CID_11697907 = -9.10kcal/mol, CID_10503282 = -9.09kcal/mol and CID_620012 = -8.53kcal/mol) with good binding energies further selected and subjected to MD Simulation to determine the stability of the protein-ligand complex. The results of the analysis indicated that all the ligands form stable complexes with the protein, although, CID_9910474 and CID_10503282 had a better stability when compared to other selected phytochemicals (CID_99615, CID_3981360, CID_620012, and CID_11697907).

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In Silico Molecular Docking and Molecular Dynamic Simulation of Potential Inhibitors of 3C-like Main Proteinase (3CLpro) from Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Using Selected African Medicinal Plants

10.26434/chemrxiv.12480434 ◽

2020 ◽

Author(s):

Sahar Qazi ◽

Mustafa Alhaji Isa ◽

Adam Mustapha ◽

Khalid Raza ◽

Ibrahim Alkali Allamin ◽

...

Keyword(s):

Molecular Docking ◽

Severe Acute Respiratory Syndrome ◽

In Silico ◽

Md Simulation ◽

Binding Energies ◽

Anacardium Occidentale ◽

Upper Respiratory Tract ◽

Ligand Complex ◽

In Silico Docking ◽

Main Protease

The Severe Acute Respiratory Syndrome 2 (SARS-CoV-2) is an infectious virus that causes mild to severe life-threatening upper respiratory tract infection. The virus emerged in Wuhan, China in 2019, and later spread across the globe. Its genome has been completely sequenced and based on the genomic information, the virus possessed 3C-Like Main Protease (3CLpro), an essential multifunctional enzyme that plays a vital role in the replication and transcription of the virus by cleaving polyprotein at eleven various sites to produce different non-structural proteins. This makes the protein an important target for drug design and discovery. Herein, we analyzed the interaction between the 3CLpro and potential inhibitory compounds identified from the extracts of Zingiber offinale and Anacardium occidentale using in silico docking and Molecular Dynamics (MD) Simulation. The crystal structure of SARS-CoV-2 main protease in complex with 02J (5-Methylisoxazole-3-carboxylic acid) and PEJ (composite ligand) (PDB Code: 6LU7,2.16Å) retrieved from Protein Data Bank (PDB) and subject to structure optimization and energy minimization. A total of twenty-nine compounds were obtained from the extracts of Zingiber offinale and the leaves of Anacardium occidentale. These compounds were screened for physicochemical (Lipinski rule of five, Veber rule, and Egan filter), Pan-Assay Interference Structure (PAINS), and pharmacokinetic properties to determine the Pharmaceutical Active Ingredients (PAIs). Of the 29 compounds, only nineteen (19) possessed drug-likeness properties with efficient oral bioavailability and less toxicity. These compounds subjected to molecular docking analysis to determine their binding energies with the 3CLpro. The result of the analysis indicated that the free binding energies of the compounds ranged between ˗5.08 and -10.24kcal/mol, better than the binding energies of 02j (-4.10kcal/mol) and PJE (-5.07kcal.mol). Six compounds (CID_99615 = -10.24kcal/mol, CID_3981360 = 9.75kcal/mol, CID_9910474 = -9.14kcal/mol, CID_11697907 = -9.10kcal/mol, CID_10503282 = -9.09kcal/mol and CID_620012 = -8.53kcal/mol) with good binding energies further selected and subjected to MD Simulation to determine the stability of the protein-ligand complex. The results of the analysis indicated that all the ligands form stable complexes with the protein, although, CID_9910474 and CID_10503282 had a better stability when compared to other selected phytochemicals (CID_99615, CID_3981360, CID_620012, and CID_11697907).

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Faculty Opinions recommendation of Comparative assessment of multiple criteria for the in silico prediction of cross-reactivity of proteins to known allergens.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.718112870.793483866 ◽

2013 ◽

Author(s):

Laura Privalle

Keyword(s):

In Silico ◽

Cross Reactivity ◽

Comparative Assessment ◽

Multiple Criteria ◽

In Silico Prediction

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Speciation of cultivated temperate and tropical Pleurotus species –an in silico prediction using conserved sequences

Mushroom Research ◽

10.36036/mr.28.1.2019.91990 ◽

2019 ◽

Vol 28 (1) ◽

Author(s):

Anupam Barh ◽

V P Sharma ◽

Shwet Kamal ◽

Mahantesh Shirur ◽

Sudheer Kumar Annepu ◽

...

Keyword(s):

In Silico ◽

In Silico Prediction ◽

Conserved Sequences ◽

Pleurotus Species

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In silico Mapping and Structure Analysis of Key Enzyme Genes in Fatty Acid Synthesis of Soybean

ACTA AGRONOMICA SINICA ◽

10.3724/sp.j.1006.2009.01942 ◽

2009 ◽

Vol 35 (10) ◽

pp. 1942-1947

Author(s):

Wan-Kun SONG ◽

Ming-Xi ZHU ◽

Yang-Lin ZHAO ◽

Jing WANG ◽

Wen-Fu LI ◽

...

Keyword(s):

Fatty Acid ◽

Structure Analysis ◽

Fatty Acid Synthesis ◽

In Silico ◽

Acid Synthesis ◽

In Silico Mapping ◽

Key Enzyme

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Quantitative Structural Activity Relationship Studies for In Silico Prediction of In Vitro Cytotoxicity of NSAIDs in Colon Cancer Cell Lines

Letters in Drug Design & Discovery ◽

10.2174/157018012802652895 ◽

2012 ◽

Vol 9 (8) ◽

pp. 755-763 ◽

Cited By ~ 1

Author(s):

Honey Goel ◽

Suresh Thareja ◽

Priyanka Malla ◽

Manoj Kumar ◽

V. R Sinha

Keyword(s):

Colon Cancer ◽

Cell Lines ◽

In Silico ◽

In Vitro Cytotoxicity ◽

Colon Cancer Cell ◽

In Silico Prediction ◽

Colon Cancer Cell Lines ◽

Structural Activity Relationship ◽

Quantitative Structural Activity Relationship

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Virtual Screening, Molecular docking and in-silico ADME-Tox analysis for identification of potential main protease (Mpro) enzyme inhibitors

Anti-Infective Agents ◽

10.2174/2211352518999201208201854 ◽

2020 ◽

Vol 18 ◽

Author(s):

Debadash Panigrahi ◽

Ganesh Prasad Mishra

Keyword(s):

Molecular Docking ◽

Virtual Screening ◽

In Silico ◽

Data Bank ◽

Future Research ◽

Reference Compound ◽

Unexpected Death ◽

Main Protease ◽

In Silico Admet

Objective:: Recent pandemic caused by SARS-CoV-2 described in Wuhan China in December-2019 spread widely almost all the countries of the world. Corona virus (COVID-19) is causing the unexpected death of many peoples and severe economic loss in several countries. Virtual screening based on molecular docking, drug-likeness prediction, and in silico ADMET study has become an effective tool for the identification of small molecules as novel antiviral drugs to treat diseases. Methods:: In the current study, virtual screening was performed through molecular docking for identifying potent inhibitors against Mpro enzyme from the ZINC library for the possible treatment of COVID-19 pandemic. Interestingly, some compounds are identified as possible anti-covid-19 agents for future research. 350 compounds were screened based on their similarity score with reference compound X77 from ZINC data bank and were subjected to docking with crystal structure available of Mpro enzyme. These compounds were then filtered by their in silico ADME-Tox and drug-likeness prediction values. Result:: Out of these 350 screened compounds, 10 compounds were selected based on their docking score and best docked pose in comparison to the reference compound X77. In silico ADME-Tox and drug likeliness predictions of the top compounds were performed and found to be excellent results. All the 10 screened compounds showed significant binding pose with the target enzyme main protease (Mpro) enzyme and satisfactory pharmacokinetic and toxicological properties. Conclusion:: Based on results we can suggest that the identified compounds may be considered for therapeutic development against the COVID-19 virus and can be further evaluated for in vitro activity, preclinical, clinical studies and formulated in a suitable dosage form to maximize their bioavailability.

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