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Record W4401110150 · doi:10.69998/j2br1

Antiviral Activities of Compounds Derived from Medicinal Plants against SARS-CoV-2 Based on Molecular Docking of Proteases

2024· article· en· W4401110150 on OpenAlexafffund
Mohamed Chebaibi, Ibrahim Mssillou, Aimad Allali, Mohammed Bourhia, Dalila Bousta, Rene Gonçalves, Hasnae Hoummani, Mourad A. M. Aboul‐Soud, Maria Augustyniak, John P. Giesy, Sanae Achour

Bibliographic record

VenueJournal of Biology and Biomedical Research. /$c Fatima Zohra Rezouki · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsBaylor University
KeywordsProteasesChemistryDocking (animal)ProteasePhytochemicalOrganosulfur compoundsBiochemistryPolyphenolEnzymeStereochemistryAntioxidantOrganic chemistry

Abstract

fetched live from OpenAlex

This work aimed to evaluate the inhibitory effect of the main polyphenols and flavonoids of Syzygium aromaticum and Citrus limon as well as the main organosulfur compounds of Allium sativum against SARS-CoV-2 6LU7 and 6Y2E proteases using in silico molecular docking analysis. Structures of 34 natural products found in three medicinal plants were docked to these two critical proteins. For 6LU7 protease, 24 compounds exhibited binding affinities greater than or equal to -6 Kcal/mol. While, for 6Y2E protease, 6 compounds exhibited binding affinities greater than or equal to -6 Kcal/mol. Molecules with a maximum binding affinity equal to -8.4 kcal/mol show good hydrogen bonds with the two proteases under investigation, 6LU7 and 6Y2E. Diosmin, ellagic acid, narirutin, neoeriocitrin, and neohesperidin were suggested as inhibitors of SARS-COV-2. These compounds might be used therapeutically as complementary medicines and/or to conceptualize new drugs against COVID-19.

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 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)0.001
metaresearch head score (Gemma)0.000
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 score0.071
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.052
GPT teacher head0.350
Teacher spread0.298 · 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 teacher head, 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

Citations24
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Biology and Biomedical Research. /$c Fatima Zohra RezoukiSame topicEssential Oils and Antimicrobial ActivityFrench-language works237,207