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All Studies   Meta Analysis    Recent:   

Unlocking the potential of phytochemicals in inhibiting SARS-CoV-2 M Pro protein - An in-silico and cell-based approach

Singh et al., Research Square, doi:10.21203/rs.3.rs-3888947/v1
Jan 2024  
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Quercetin for COVID-19
23rd treatment shown to reduce risk in July 2021
 
*, now with p = 0.0031 from 11 studies.
No treatment is 100% effective. Protocols combine treatments. * >10% efficacy, ≥3 studies.
4,500+ studies for 81 treatments. c19early.org
In Silico and In Vitro study including quercetin and curcumin derivatives as potential SARS-CoV-2 main protease (Mpro) inhibitors. Molecular dynamics simulations and virtual screening identified quercetin and curcumin derivatives demethoxycurcumin and hexahydrocurcumin as potential binders of Mpro. Demethoxycurcumin was tested in vitro, showing significant inhibitory activity against SARS-CoV-2, with no cytotoxicity observed.
59 preclinical studies support the efficacy of quercetin for COVID-19:
In Silico studies predict inhibition of SARS-CoV-2, or minimization of side effects, with quercetin or metabolites via binding to the spikeA,2,3,15,17,18,23,31,32,34,35,52,53, MproB,2,4,6,8,10,11,13,16,17,23,27,29-31,35,36,38,53,54, RNA-dependent RNA polymeraseC,2,25, PLproD,30,38, ACE2E,15,16,21,30,34,53, TMPRSS2F,15, helicaseG,22,27, endoribonucleaseH,32, cathepsin LI,19, Wnt-3J,15, FZDK,15, LRP6L,15, ezrinM,33, ADRPN,31, NRP1O,34, EP300P,9, PTGS2Q,16, HSP90AA1R,9,16, matrix metalloproteinase 9S,24, IL-6T,14,28, IL-10U,14, VEGFAV,28, and RELAW,28 proteins. In Vitro studies demonstrate efficacy in Calu-3X,41, A549Y,14, HEK293-ACE2+Z,48, Huh-7AA,18, Caco-2AB,40, Vero E6AC,12,35,40, mTECAD,43, and RAW264.7AE,43 cells. Animal studies demonstrate efficacy in K18-hACE2 miceAF,45, db/db miceAG,43,51, BALB/c miceAH,50, and rats55. Quercetin reduced proinflammatory cytokines and protected lung and kidney tissue against LPS-induced damage in mice50.
Study covers curcumin and quercetin.
Singh et al., 29 Jan 2024, preprint, 7 authors. Contact: khushboo.singh@amway.com.
In Silico studies are an important part of preclinical research, however results may be very different in vivo.
This PaperQuercetinAll
Unlocking the potential of phytochemicals in inhibiting SARS-CoV-2 M Pro protein - An in-silico and cell-based approach
Khushboo Singh, J J Patten, Andrea Dimet, Robert A Davey, Stanley J Watowich, Amit Chandra, Jesse Leverett
doi:10.21203/rs.3.rs-3888947/v1
The main protease (M Pro ) of SARS-CoV-2 plays a crucial role in viral replication and is a prime target for therapeutic interventions. Phytochemicals, known for their antiviral properties, have been previously identi ed as potential M Pro inhibitors in several in silico studies. However, the e cacy of these remains in question owing to the inherent exibility of the M Pro binding site, posing challenges in selecting suitable protein structures for virtual screening. In this study, we conducted an extensive analysis of the M Pro binding pocket, utilizing molecular dynamics (MD) simulations to explore its conformational diversity. Based on pocket volume and shape-based clustering, ve representative protein conformations were selected for virtual screening. Virtual screening of a library of ~ 48,000 phytochemicals suggested 39 phytochemicals as potential M Pro inhibitors. Based on subsequent MM-GBSA binding energy calculations and ADMET property predictions, ve compounds were advanced to cell-based viral replication inhibition assays, with three compounds (demethoxycurcumin, shikonin, and withaferin A) exhibiting signi cant (EC50 < 10 uM) inhibition of SARS-CoV-2 replication. Our study provides an understanding of the binding interactions between these phytochemicals and M Pro , contributing signi cantly to the identi cation of promising M Pro inhibitors. Furthermore, beyond its impact on therapeutic development against SARS-CoV-2, this research highlights a crucial role of proper nutrition in the ght against viral infections. Phytochemical Name Docking scores Conformation 1 Conformation 2 Conformation 3 Conformation 4 Conformation 5 1,3,6-Tri-O-Galloyl-Beta-D-Glucose -7.6 -8.8 -11.1 -7.5 -10.1 2'-Acetylacteoside -8.6 -9.5 -12.1 -13.4 -7.6 2''-O-Acetylrutin -10.3 -9.6 -12.2 -10.8 -10.4 *AHDPH -8.1 -9.0 -11.6 -7.5 -9.0 Balanophotannin E -7.5 -11.0 -12.9 -9.9 -8.4 **DDHHG -9.7 -8.3 -10.9 -11.3 -8.6 ***DHMMP-TRTH-TMMO-Chr-One -9.7 -10.5 -10.7 -9.1 -9.9 Eriodictyol 7-O-Sophoroside -12.6 -9.3 -10.0 -11.1 -10.0 Forsythiaside -10.3 -12.6 -14.3 -14.6 -9.2 Hyperin 6''-[glucosyl-(1->3)-rhamnoside] -9.7 -10.9 -15.9 -12.1 -11.9 Kaempferol 3-(3R-glucosylrutinoside) -10.0 -10.6 -12.0 -11.1 -8.5 Luteolin 7-rutinoside -9.8 -9.4 -14.4 -12.0 -9.9 Narcissin -9.7 -10.5 -10.7 -9.1 -9.9 Pectolinarin -8.9 -7.7 -13.9 -8.5 -7.5 Plantagineoside C -9.4 -10.3 -13.3 -10.4 -9.3 Quercetin 3-glucoside2''-gallate -7.8 -9.2 -12.1 -10.6 -7.5 Quercetin-3-o-rutinose -12.2 -11.0 -11.1 -11.5 -11.4 Salvianolic Acid L (SAL) -9.1 -8.2 -13.3 -11.3 -7.6 Shikonin -8.1 -8.4 -8.6 -8.9 -9.5 Shimobashiric Acid C (SAC) -8.2 -8.7 -10.5 -9.6 -10. 2 *AHDPH = (3R,5R)-3-Acetoxy-5-Hydroxy-1,7-Bis(3,4-Dihydroxyphenyl)Heptane. **DDHHG = (3R,5R)-3,5-Dihydroxy-1-(3,4-Dihydroxyphenyl)-7-(4-Hydroxyphenyl)-Heptane 3-O-Beta-D-Glucopyranoside.
For a comprehensive understanding of the model speci cations, validation, and performance, please refer to the AP11.0 user manual and relevant publications 74, 75 . Cytoxicity Assay Vero cells were seeded using a multiDrop combi liquid dispenser (Thermo) into 384-well plates at a density of 500 cells/well suspended in 50 µL of media. Cells were allowed to recover and fully attach overnight (approximately 16 hours), at which point library compounds were dispensed into wells using an Echo 550 acoustic dispenser (Labcyte). A total of six nal concentrations where tested (50 µM, 25 µM, 12.5 µM, 6.25 µM, 3.125 µM, and 1.5625 µM) and wells were back lled with DMSO such that all wells contained a xed ratio of DMSO. Compounds were incubated with cells for 1 hour prior to addition of virus and then for an additional 24 hours, then xed with 10% formalin, permeabilized 0.1% Triton X-100, washed, and stained for SARS-CoV-2 N protein using a speci c antibody (Sino Biological # MM05) and uorescently labelled secondary antibody. Cells were counter stained with Hoechst 33342 to detect cell nuclei, washed, and imaged with a Cytation 1 (Biotek) automated. Each image was then analyzed with a custom work ow in Cell Pro ler (Broad Inst., Boston, MA) which involved counting of cell nuclei and infected cells. At least 4 replicates were used to construct dose response curves. Statistics and data normalization The rate index is calculated from cell counts using the following formula: Where X c..
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' 'Phytochemicals, known for their antiviral properties, have been previously identified as ' 'potential M<jats:sup>Pro</jats:sup> inhibitors in several in silico studies. However, the ' 'efficacy of these remains in question owing to the inherent flexibility of the ' 'M<jats:sup>Pro</jats:sup> binding site, posing challenges in selecting suitable protein ' 'structures for virtual screening. In this study, we conducted an extensive analysis of the ' 'M<jats:sup>Pro</jats:sup> binding pocket, utilizing molecular dynamics (MD) simulations to ' 'explore its conformational diversity. Based on pocket volume and shape-based clustering, five ' 'representative protein conformations were selected for virtual screening. Virtual screening ' 'of a library of ~\u200948,000 phytochemicals suggested 39 phytochemicals as potential ' 'M<jats:sup>Pro</jats:sup> inhibitors. 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