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Discovery of lead natural products for developing pan-SARS-CoV-2 therapeutics

2022· article· en· W4311089805 on OpenAlexafffund
Jimena Pérez‐Vargas, Tirosh Shapira, Andrea D. Olmstead, Ivan Villanueva, Connor A.H. Thompson, Siobhan Ennis, Guang Gao, Joshua De Guzman, David E. Williams, Meng Wang, Aaleigha Chin, Diana Bautista-Sánchez, Olga Agafitei, Paul N. Levett, Xuping Xie, Genoveffa Nuzzo, Vítor F. Freire, Jairo I. Quintana-Bulla, Darlon I. Bernardi, Juliana R. Gubiani, Virayu Suthiphasilp, Achara Raksat, Pornphimol Meesakul, Isaraporn Polbuppha, Sarot Cheenpracha, Wuttichai Jaidee, Kwanjai Kanokmedhakul, Chavi Yenjai, Boonyanoot Chaiyosang, Helder Lopes Teles, Emiliano Manzo, Angelo Fontana, Richard Leduc, Pierre‐Luc Boudreault, Roberto G. S. Berlinck, Surat Laphookhieo, Somdej Kanokmedhakul, Ian Tietjen, Artem Cherkasov, Mel Krajden, Ivan R. Nabi, Masahiro Niikura, Pei‐Yong Shi, Raymond J. Andersen, François Jean

Bibliographic record

VenueAntiviral Research · 2022
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsBC Centre for Disease ControlUniversité de SherbrookeSimon Fraser UniversityUniversity of British Columbia
FundersMitacsNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health ResearchGenome British Columbia
KeywordsBafilomycinVirologySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Vero cellEC50Monoclonal antibodyCell cultureChemistryMicrobiologyIn vitroCoronavirus disease 2019 (COVID-19)BiologyVirusMedicineBiochemistryAntibodyImmunologyInfectious disease (medical specialty)Disease

Abstract

fetched live from OpenAlex

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), remains a global public health crisis. The reduced efficacy of therapeutic monoclonal antibodies against emerging SARS-CoV-2 variants of concern (VOCs), such as omicron BA.5 subvariants, has underlined the need to explore a novel spectrum of antivirals that are effective against existing and evolving SARS-CoV-2 VOCs. To address the need for novel therapeutic options, we applied cell-based high-content screening to a library of natural products (NPs) obtained from plants, fungi, bacteria, and marine sponges, which represent a considerable diversity of chemical scaffolds. The antiviral effect of 373 NPs was evaluated using the mNeonGreen (mNG) reporter SARS-CoV-2 virus in a lung epithelial cell line (Calu-3). The screening identified 26 NPs with half-maximal effective concentrations (EC50) below 50 μM against mNG-SARS-CoV-2; 16 of these had EC50 values below 10 μM and three NPs (holyrine A, alotaketal C, and bafilomycin D) had EC50 values in the nanomolar range. We demonstrated the pan-SARS-CoV-2 activity of these three lead antivirals against SARS-CoV-2 highly transmissible Omicron subvariants (BA.5, BA.2 and BA.1) and highly pathogenic Delta VOCs in human Calu-3 lung cells. Notably, holyrine A, alotaketal C, and bafilomycin D, are potent nanomolar inhibitors of SARS-CoV-2 Omicron subvariants BA.5 and BA.2. The pan-SARS-CoV-2 activity of alotaketal C [protein kinase C (PKC) activator] and bafilomycin D (V-ATPase inhibitor) suggest that these two NPs are acting as host-directed antivirals (HDAs). Future research should explore whether PKC regulation impacts human susceptibility to and the severity of SARS-CoV-2 infection, and it should confirm the important role of human V-ATPase in the VOC lifecycle. Interestingly, we observed a synergistic action of bafilomycin D and N-0385 (a highly potent inhibitor of human TMPRSS2 protease) against Omicron subvariant BA.2 in human Calu-3 lung cells, which suggests that these two highly potent HDAs are targeting two different mechanisms of SARS-CoV-2 entry. Overall, our study provides insight into the potential of NPs with highly diverse chemical structures as valuable inspirational starting points for developing pan-SARS-CoV-2 therapeutics and for unravelling potential host factors and pathways regulating SARS-CoV-2 VOC infection including emerging omicron BA.5 subvariants.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentalhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.017
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.211
GPT teacher head0.460
Teacher spread0.249 · 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

Labeled directly by 2 models reading the full record.

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

Citations18
Published2022
Admission routes2
Has abstractyes

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