Interactions between Phytochemical Components of Sutherlandia Frutescens and the Antiretroviral, Atazanavir In Vitro: Implications for Absorption and Metabolism
Bibliographic record
Abstract
PURPOSE: African traditional medicinal plants, such as Sutherlandia frutescens have the potential to interact pharmacokinetically with the protease inhibitor class of antiretrovirals, thereby impacting on their safety and efficacy. The effects of extracts and phytochemical components of Sutherlandia frutescens, on the in vitro absorption and metabolism of the protease inhibitor, atazanavir were thus investigated. METHODS: Aqueous and methanolic extracts of Sutherlandia frutescens were prepared by freeze-drying of hot water and methanol decoctions of Sutherlandia frutescens plant material respectively, whilst crude triterpenoid glycoside and flavonol glycoside fractions were isolated by solvent extraction and subsequent column chromatography. Atazanavir was quantitated in the absence or presence of these compounds as well as commercially available purported constituents of Sutherlandia frutescens, namely, L-canavanine, L-GABA and D-pinitol, after a one hour co-incubation in Caco-2 cell monolayers and human liver microsomes. RESULTS: The triterpenoid and flavonol glycoside fractions were found to be present in the aqueous and methanolic extracts of Sutherlandia frutescens and were shown to contain the sutherlandiosides and sutherlandins known to be present in Sutherlandia frutescens. The aqueous extract and D-pinitol significantly reduced atazanavir accumulation by Caco-2 cells, implying a decrease in atazanavir absorption, whilst the opposite was true for the triterpenoid glycoside fraction. Both the aqueous and methanolic extracts inhibited atazanavir metabolism in human liver microsomes, whilst enhanced atazanavir metabolism was exhibited by the triterpenoid glycoside fraction. CONCLUSIONS: The extracts and phytochemical components of Sutherlandia frutescens influenced the accumulation of atazanavir by Caco-2 cells and also affected ATV metabolism in human liver microsomes. These interactions may have important implications on the absorption and metabolism and thus the overall oral bioavailability of atazanavir.
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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".