Thiopental-Inspired alkylpyrimidines as dual-target antimicrobial agents: Synthesis, biological activity, and molecular docking validation
Bibliographic record
Abstract
Alkylpyrimidine derivatives, particularly thiopental-based analogs, have emerged as promising scaffolds for antimicrobial drug development. In this study, we designed and synthesized a series of novel thiopental-pyrimidine hybrids (3a–c, 4) through efficient condensation reactions, and characterized these compounds by using NMR, IR, and mass spectrometry. Antimicrobial screening revealed significant activity against clinically relevant strains: derivative 3a exhibited selective inhibition of Bacillus subtilis (MIC: 10.5±0.4 mg/mL) and Escherichia coli (MIC: 22.1±0.3 mg/mL), while 3c showed potent antifungal effects against Candida albicans (MIC: 11.6±0.4 mg/mL). Molecular docking studies elucidated the mechanistic basis of this activity, with 3a binding to penicillin-binding protein (PBP; −6.4 kcal/mol) via hydrogen bonds (SER392) and hydrophobic interactions (TYR430, PRO660), and 3c coordinating with the heme iron of CYP51 (−7.8 kcal/mol) akin to fluconazole. Notably, 3c thioether linkage facilitated π-cation/anion interactions with PHE463, rationalizing its antifungal specificity. Structure-activity relationships (SAR) underscored the critical roles of electron-deficient pyrimidine cores for antibacterial activity and sulfur moieties for antifungal action. These findings position thiopental-pyrimidine hybrids as versatile leads for combating microbial resistance, with 3c representing a particularly promising antifungal candidate. Our integrated synthetic, biological, and computational approach provides a blueprint for optimizing these scaffolds for clinical translation.
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".