Inhibitory activities of baicalin against renin and angiotensin-converting enzyme
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
CONTEXT: Baicalin has been characterized as the active compound and quality control marker in Scutellaria baicalensis Georgi, traditionally used as a hypotensive herb. OBJECTIVES: To investigate the inhibitory activities of baicalin against renin and angiotensin-I converting enzyme (ACE) and their molecule mechanism of interactions. METHODS: The fluorescence method using renin substrate 1(R-2932) and the spectroscopy method by Cushman were used to determine renin and ACE activities, respectively. The fluorescence quench techniques were used to characterize their interactions. RESULTS: The results showed that baicalin inhibited renin activity with an IC(50) value of 120.36 µM and inhibited ACE activity with an IC(50) value of 2.24 mM in vitro. The fluorescence emission of both renin and ACE were efficiently quenched by baicalin and a complete quenching was achieved at a high concentration of baicalin. Furthermore, baicalin was more effective in quenching the fluorescence of renin (K(SV) = 60 × 10(3) M(-1)) than ACE (K(SV) = 17.1 × 10(3) M(-1)). The quenching of fluorescence of renin and ACE involved static interactions, which was characterized by the formation of quencher-enzyme complex. The baicalin-renin complex formed through three-sites binding including the active site with a binding constant of 796.15 × 10(13) M(-1), but there was only one binding site for the baicalin-ACE complex with a much smaller binding constant of 6.8 × 10(5) M(-1). CONCLUSION: The inhibition activity of baicalin against renin was a result of the formation of stable complex through multisites binding including the active site, which could explain the higher inhibitory efficiency.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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