Synthesis, Characterization, and Computational Investigation of 2,5-Bis(2-Methyl-1H-benzimidazol-5-yl)-1,3,4-oxadiazole: Quantum Chemical Analysis, ADME Prediction, Molecular Docking, and MD-Based Corrosion Study for Photonic and Therapeutic Applications
Bibliographic record
Abstract
This study presents the synthesis and characterization of 2,5-bis(2-methyl-1H-benzimidazol-5-yl)-1,3,4-oxadiazole, using 1H NMR, 13C NMR, mass spectrometry and FTIR-ATR infrared spectroscopy. Quantum chemical analysis revealed that P1 possesses a balanced electrophilic–nucleophilic profile, enabling interactions with diverse biological targets. Its HOMO–LUMO gap and electronic stability suggest potential applications in photonic devices. ADMET predictions indicated favorable pharmacokinetics and overall drug-likeness. Molecular docking demonstrated high binding affinities toward anticancer, antibacterial, and antifungal proteins, with P1 reproducing reference ligand binding modes while forming additional stabilizing contacts. Molecular Dynamics simulations captured the thermal motion and conformational flexibility of P1 on the Fe(110) surface, while Monte Carlo simulations identified energy-minimized, compact adsorption conformations. Both approaches confirmed thermodynamically favorable chemisorption, stabilized by direct surface interactions and solvent/ionic contributions. Together, these findings highlight P1 as a dual-purpose scaffold, combining selective biological activity, favorable electronic properties, and strong surface interactions. This integrated computational study supports its potential for both therapeutic development and optoelectronic application.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".