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Record W3157743342 · doi:10.1101/2021.04.29.442010

The natural stilbenoid (–)-hopeaphenol inhibits cellular entry of SARS-CoV-2 USA-WA1/2020, B.1.1.7 and B.1.351 variants

2021· preprint· en· W3157743342 on OpenAlexfundno aff
Ian Tietjen, Joel Cassel, Emery T. Register, Xiang Zhou, Troy E. Messick, Frederick Keeney, Lily Lu, Karren D. Beattie, Topul Rali, Hildegund C.J. Ertl, Joseph M. Salvino, Rohan A. Davis, Luis J. Montaner

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMedical Research CouncilSimon Fraser UniversityAustralian Research CouncilCanadian Institutes of Health ResearchGriffith University
KeywordsIC50Viral entryCytopathic effectVero cellCytotoxicityIn vitroSmall moleculeChemistryReceptorVirologyBiologyBinding siteViral replicationVirusBiochemistry

Abstract

fetched live from OpenAlex

Abstract Antivirals are urgently needed to combat the global SARS-CoV-2/COVID-19 pandemic, supplement existing vaccine efforts, and target emerging SARS-CoV-2 variants of concern. Small molecules that interfere with binding of the viral spike receptor binding domain (RBD) to the host ACE2 receptor may be effective inhibitors of SARS-CoV-2 cell entry. Here we screened 512 pure compounds derived from natural products using a high-throughput RBD/ACE2 binding assay and identified (–)-hopeaphenol, a resveratrol tetramer, in addition to vatalbinoside A and vaticanol B, as potent and selective inhibitors of RBD/ACE2 binding and viral entry. For example, (–)-hopeaphenol disrupted RBD/ACE2 binding with a 50% inhibitory concentration (IC50) of 0.11 μM in contrast to an IC50 of 28.3 μM against the unrelated host ligand/receptor binding pair PD-1/PD-L1 (selectivity index = 257.3). When assessed against the USA-WA1/2020 variant, (–)-hopeaphenol also inhibited entry of a VSVΔG-GFP reporter pseudovirus expressing SARS-CoV-2 spike into ACE2-expressing Vero-E6 cells and in vitro replication of infectious virus in cytopathic effect assays (IC50 = 10.2 μM) without cytotoxicity. Notably, (–)- hopeaphenol also inhibited two emerging variants of concern originating from the United Kingdom (B.1.1.7) and South Africa (B.1.351) in both cytopathic effect and spike-containing pseudovirus assays with similar (B.1.1.7) or improved (B.1.351) efficacies over the USA- WA1/2020 variant. These results identify (–)-hopeaphenol and related stilbenoid analogues as potent and selective inhibitors of viral entry across multiple SARS-CoV-2 variants including those with increased infectivity and/or reduced susceptibility to existing vaccines. Importance SARS-CoV-2 antivirals are needed to supplement existing vaccine efforts and target emerging viral variants with increased infectivity or reduced susceptibility to existing vaccines. Here we show that (–)-hopeaphenol, a naturally-occurring stilbenoid compound, in addition to its analogues vatalbinoside A and vaticanol B, inhibit SARS-CoV-2 by blocking the interaction of the viral spike protein with the cellular ACE2 entry receptor. Importantly, in addition to inhibiting the early USA-WA1/2020 SARS-CoV-2 variant, hopeaphenol also inhibits emerging variants of concern including B.1.1.7 (“United Kingdom variant”) and B.1.351 (“South Africa variant”), with improved efficacy against B.1.351. (–)-Hopeaphenol therefore represents a new antiviral lead against infection from multiple SARS-CoV-2 variants.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.274
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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