Investigating the potential of 6-substituted 3-formyl chromone derivatives as anti-diabetic agents using in silico methods
Why this work is in the frame
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Bibliographic record
Abstract
Abstract In exploring nature's potential in addressing diabetes-related conditions, this study investigates the therapeutic capabilities of 3-formyl chromone derivatives. Utilizing in silico methodologies, we focus on 6-substituted 3-formyl chromone derivatives (1–16) to assess their therapeutic potential in treating diabetes. The research examined the formyl group at the chromone’s C-3 position. ADMET, biological activities, were conducted along with B3LYP calculations using 3 different basis sets. The analogues were analyzed based on their parent structure obtained from PubChem. The HOMO–LUMO gap confirmed the bioactive nature of the derivatives, NBO analysis was performed to understand the charge transfer. PASS prediction revealed that 3-formyl chromone derivatives are potent aldehyde oxidase inhibitors, insulin inhibitors, HIF1A expression inhibitors, and histidine kinase. Molecular docking studies indicated that the compounds had a strong binding affinity with proteins, including CAD, BHK, IDE, HIF-α, p53, COX, and Mpro of SARS-CoV2. 6-isopropyl-3-formyl chromone (4) displayed the highest affinity for IDE, with a binding energy of − 8.5 kcal mol −1 . This result outperformed the affinity of the reference standard dapagliflozin (− 7.9 kcal mol −1 ) as well as two other compounds that target human IDE, namely vitexin (− 8.3 kcal mol −1 ) and myricetin (− 8.4 kcal mol −1 ). MD simulations were revealed RMSD value between 0.2 and 0.5 nm, indicating the strength of the protein–ligand complex at the active site.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it