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Record W3111474440 · doi:10.3906/kim-2005-19

Computational and biological studies of novel thiazolyl coumarin derivatives synthesized through Suzuki coupling

2020· article· en· W3111474440 on OpenAlexfundno aff
Shaista Parveen, Saima Kalsoom, Rifhat Bibi, Ambreen ASGHAR, Abdul Hameed, Waqar Ahmed, Abbas Hassan

Bibliographic record

VenueTURKISH JOURNAL OF CHEMISTRY · 2020
Typearticle
Languageen
FieldChemistry
TopicSynthesis and biological activity
Canadian institutionsnot available
FundersHigher Education Commission, PakistanUniversity of Ottawa
KeywordsChemistryThiazoleCoumarinArylCombinatorial chemistryTrichoderma harzianumAntimicrobialSuzuki reactionYield (engineering)Antibacterial activityDocking (animal)In vitroStereochemistryOrganic chemistryBiochemistryBacteria

Abstract

fetched live from OpenAlex

The current investigation presents the synthesis, computational molecular-docking and biological activity studies of arylated thiazole coumarins. Aryl substituted thiazolyl coumarin derivatives were synthesized via Suzuki cross-coupling reaction. A detailed reaction condition optimization revealed that the Pd-PEPPSI-IPent precatalyst in only 2 mol% loading resulted in the desired product with high yield. The aim of this study was to examine the antimicrobial behavior of thiazole coumarin derivatives through in vitro and in silico studies. All the compounds showed activity against both antibacterial strains, Staphylococcus aureus and Escherichia coli, except 5d. Similarly, the compounds 5a, 5b, and 5d were found to be active against Trichoderma harzianum. The compound 5d of this series was found to have a higher activity with MIC 125 mg/ml against Trichoderma harzianum. Molecular studies showed the high activities of these compounds are due to the presence of strong H-bonding and π- π interaction with their respective targets. A good correlation was observed between computational and in vitro studies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.125
GPT teacher head0.311
Teacher spread0.186 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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Same venueTURKISH JOURNAL OF CHEMISTRYSame topicSynthesis and biological activityFrench-language works237,207