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Record W3035046940 · doi:10.21577/0103-5053.20200112

Virtual Screening of Secondary Metabolites of the Family Velloziaceae J. Agardh with Potential Antimicrobial Activity

2020· article· en· W3035046940 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Brazilian Chemical Society · 2020
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPhytochemistry and Bioactivity Studies
Canadian institutionsDiscovery Air (Canada)
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsAntimicrobialVirtual screeningChemistryBiologyMicrobiologyBiochemistryDrug discovery

Abstract

fetched live from OpenAlex

The objective of this work was to carry out a bibliographic survey of secondary metabolites isolated from the Velloziaceae family, creating a bank of compounds. After the bank was created, four prediction models for potentially active compounds against pathogenic microorganisms (Candida albicans, Escherichia coli, Pseudomonas aeruginosa and Salmonella sp.) were obtained trying to identify which metabolites would be more active against the strains. Four sets of compounds with known activity for microorganisms were selected for the construction of predictive models from the CHEMBL database. Another bank with 163 unique molecules isolated from the Velloziaceae family was built. The Volsurf+ v.1.0.7 software obtained the molecular descriptors and Knime 3.5 generated the in silico model. The performances of the internal and external tests were also analyzed. The study contributed through the virtual screening of a bank of metabolites to select several compounds with potential antimicrobial activity, highlighting the biflavonoid amentoflavone which showed potential activity against the four strains.

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.

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)0.000
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 score0.008
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.046
GPT teacher head0.325
Teacher spread0.278 · 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