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Record W4287010204 · doi:10.3390/ijms23158117

An Overview of the Biological Evaluation of Selected Nitrogen-Containing Heterocycle Medicinal Chemistry Compounds

2022· review· en· W4287010204 on OpenAlexafffund
Oluwakemi Ebenezer, Maryam Amra. Jordaan, Gea Carena, Tommaso Bono, Michael Shapi, Jack A. Tuszyński

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2022
Typereview
Languageen
FieldChemistry
TopicSynthesis of Tetrazole Derivatives
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPharmacophoreHeteroatomChemistryRing (chemistry)ImidazoleDrug discoveryHeterocyclic compoundCombinatorial chemistryOrganic chemistryStereochemistryBiochemistry

Abstract

fetched live from OpenAlex

Heterocyclic compounds are a class of compounds of natural origin with favorable properties and hence have major pharmaceutical significance. They have an exceptional adroitness favoring their use as diverse smart biomimetics, in addition to possessing an active pharmacophore in a complex structure. This has made them an indispensable motif in the drug discovery field. Heterocyclic compounds are usually classified according to the ring size, type, and the number of heteroatoms present in the ring. Among different heterocyclic ring systems, nitrogen heterocyclic compounds are more abundant in nature. They also have considerable pharmacological significance. This review highlights recent pioneering studies in the biological assessment of nitrogen-containing compounds, namely: triazoles, tetrazoles, imidazole/benzimidazoles, pyrimidines, and quinolines. It explores publications between April 2020 and February 2022 and will benefit researchers in medicinal chemistry and pharmacology. The present work is organized based on the size of the heterocyclic ring.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.189
GPT teacher head0.422
Teacher spread0.233 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations146
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Molecular SciencesSame topicSynthesis of Tetrazole DerivativesFrench-language works237,207