Dereplication of known pregnane glycosides and structural characterization of novel pregnanes in <i>Marsdenia tenacissima</i> by high‐performance liquid chromatography and electrospray ionization‐tandem mass spectrometry
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Bibliographic record
Abstract
In the search for novel natural products in plants, particularly those with potential bioactivity, it is important to efficiently distinguish novel compounds from previously isolated, known compounds, a process known as dereplication. In this study, electrospray ionization-multiple stage tandem mass spectrometry (ESI-MS(n)) was used to study the behaviour of 12 pregnane glycosides and genins previously isolated from Marsdenia tenacissima, a traditional Chinese medicinal plant, as a basis for dereplication of compounds in a plant extract. In addition to [M + Na](+) and [M + NH(4)](+) ions, a characteristic [M-glycosyl + H](+) ion was observed in full-scan mode with in-source fragmentation. Sequential in-trap collision-induced dissociation of [M + Na](+) ions from 11,12-diesters revealed consistent preferred losses of substituents first from C-12, then from C-11, followed by losses of monosaccharide fragments from the C-3 tri- and tetrasaccharide substituents. A crude methanol extract of M. tenacissima stems was analysed using high-performance liquid chromatography coupled to ESI-MS. Several previously isolated pregnane glycosides were dereplicated, and the presence of an additional nine novel pregnane glycosides is predicted on the basis of the primary and fragment ions observed, including two with a previously unreported C(4)H(7)O C-11/C-12 substituent of pregnane glycosides. This study is the first report of prediction of the structures of novel pregnane glycosides in a crude plant extract by a combination of in-source fragmentation and in-trap collision-induced dissociation and supports the usefulness of LC-ESI-MS(n) not only for dereplication of active compounds in extracts of medicinal plants but also for detecting the presence of novel related compounds.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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