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Record W4414071106 · doi:10.5267/j.ccl.2025.7.002

1,2,4-triazole-chalcone and derivatives as antiproliferative agents: Quantum chemical studies, molecular docking, ADME-Tox and MD simulation

2025· article· en· W4414071106 on OpenAlexvenueno aff
Hanane Zaki, Mohamed Ouabane, Soumaya Aissaoui, Marwa Alaqarbeh, Mohammed Bouachrıne

Bibliographic record

VenueCurrent Chemistry Letters · 2025
Typearticle
Languageen
FieldChemistry
TopicSynthesis and biological activity
Canadian institutionsnot available
Fundersnot available
KeywordsMolecular dynamicsBinding affinitiesAffinitiesQuantum chemicalMolecular modelAmino acid residueMolecular mechanicsDocking (animal)

Abstract

fetched live from OpenAlex

The investigation of 1,2,4-triazole-chalcone has sparked immense interest due to their promising biological activities. These compounds, labeled 10C-10S, were synthesized and characterized by Jinjing et al., specifically focusing on their potential applications in biological settings, particularly their antiproliferative properties. Strategic exploration by computational chemistry techniques such as DFT calculations, molecular docking, and molecular dynamics with empirical findings proved pivotal in unraveling the multifaceted properties of these organic molecules. Additionally, molecular docking studies were conducted to elucidate the antiproliferative effects and analyze the potential binding modes of the compounds with specific amino acid residues in proteins. Rigorous comparisons between theoretical and experimental results yielded comprehensive insights into the properties of these compounds. We chose two molecules, C (the most active) and E (the least active), which have affinities of -7.689 and -7.526 kcal/mol, respectively, to test how stable they are with the EGFR receptor (PDB entry code: 6Z4B). Molecular dynamics simulations over 100 ns revealed more stable energies, with ΔG_Bind = -25.135 Kcal/mol and ΔG_Bind_vdW = -30.644 Kcal/mol.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.040
GPT teacher head0.340
Teacher spread0.300 · 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.

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

Citations2
Published2025
Admission routes1
Has abstractyes

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