Cyclization of Polyphenols from Natural Products: Potential Pharmacological and Toxicological Implications
Bibliographic record
Abstract
Previously our group identified that the dicatechol lignan nordihydroguaiaretic acid (NDGA) can undergo spontaneous autoxidation and intramolecular cyclization at pH 7.4 to form a dibenzocyclooctadiene (cNDGA). We also observed that autoxidation of NDGA or cNDGA was required for inhibition of -synuclein aggregation in vitro, a protein associated with Parkinson’s disease. \nA number of dicatechol ethanes have been shown to inhibit -synuclein aggregation in vitro and we propose that the anti-aggregation effects are the result of autoxidation/ intramolecular cyclization. My first goal was to determine if dicatechol ethanes could spontaneously autoxidize/ cyclize and inhibit -synuclein aggregation in vitro. \nIn order to assess the formation of 6-membered ring dicatechols, I synthesized and characterized three diphenylethane analogs with 0, 2 or 4 methyl groups on the 2-carbon linker. I determined that all of the analogs spontaneously cyclize at pH 7.4 into the corresponding dibenzocyclohexadienes which were also oxidatively labile and formed additional oxidation products. The rate of cyclization to form dibenzocyclohexadienes is 10-30 times faster than for dibenzocyclooctadienes and both the diphenylethanes and dibenzocyclohexadienes inhibit -synuclein aggregation in vitro.\n A second goal of my project was to study the metabolism of quebecol, a triphenylethane natural product isolated from maple syrup production which is under investigation as a chemopreventive and chemotherapeutic, although there are no reports on the hepatic metabolism of quebecol. In order to assess hepatic metabolism, I synthesized and isolated quebecol and investigated its in vitro metabolism in rat liver microsomes (RLM) and human liver microsomes (HLM). I anticipated that phase II metabolism would predominate, and I observed formation of three glucuronide metabolites in both RLM and HLM. To determine the hepatic contribution to first-pass glucuronidation, I validated an HPLC-UV method following FDA and EMA guidelines (selectivity, linearity, accuracy and precision) to quantify quebecol metabolism in microsomes. In vitro enzyme kinetics were performed for quebecol glucuronidation in HLM including 8 concentrations from 5-30 M. I determined a Michaelis-Menten constant (KM) of 5.1 M, intrinsic clearance (Clint) of 0.04 mL/min/mg and maximum velocity (Vmax) of 0.22 mol/min/mg. \nIn contrast I was unable to detect any P450 metabolites of quebecol in either RLM or HLM. In spite of the presence of three phenols that could form para-quinone methides, glutathione (GSH) trapping experiments provided no evidence for reactive intermediate formation. To confirm the absence of para-quinone methides I attempted to prepare standards using MnO2 as oxidant and trapping with GSH. Rather than observe the expected para-quinone methides, instead I observed ortho-quinone formation resulting from MnO2-mediated dealkylation. Together with extensive phase II glucuronidation, this suggests that the risk of reactive intermediate formation from quebecol is negligible.
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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) | 0.002 | 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".