1,2,4-triazole-chalcone and derivatives as antiproliferative agents: Quantum chemical studies, molecular docking, ADME-Tox and MD simulation
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".