Molecular Formula Analysis by an MS/MS/MS Technique To Expedite Dereplication of Natural Products
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Bibliographic record
Abstract
A facile and sensitive mass spectrometric method has been developed for the dereplication of natural products. The method provides information about the molecular formula and substructure of a precursor molecule and its fragments, which are invaluable aids in dereplication of natural products at their early stages of purification and characterization. Collision-induced MS/MS technique is used to fragment a precursor ion into several product ions, and individual product ions are selected and subjected to collision-induced MS/MS/MS analysis. This method enables the identification of the fragmentation pathway of a precursor molecule from its first-generation fragments (MS/MS), through to the nth generation product ions (MSn). It also allows for the identification of the corresponding neutral products released (neutral losses). Elements used in the molecular formula analysis include C, H, N, O, and S, as most natural products are constituted by these five elements. High-resolution mass separation and accurate mass measurements afforded the unique identification of molecular formula of small neutral products. Through sequential add-up of the molecular formulas of the small neutral products, the molecular formula of the precursor ion and its productions were uniquely determined. The molecular formula of the precursor molecule was then reversely used to identify or confirm the molecular formula of the neutral products and that of the productions. The molecular formula of the neutral fragments allowed for the identification of substructures, leading to a rapid and efficient characterization of precursor natural product. The method was applied to paclitaxel (C47H51NO14; 853 amu) to identify its molecular formula and its substructures, and to characterize its potential fragmentation pathways. The method was further validated by correctly identifying the molecular formula of minocycline (C23H27N3O7; 457 amu) and piperacillin (C23H27N5O7S; 517 amu).
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it