Effects of electrospray mechanisms and structural relaxation on polylactide ion conformations in the gas phase: insights from ion mobility spectrometry and molecular dynamics simulations
Bibliographic record
Abstract
Recent advances in molecular dynamics (MD) simulations have made it possible to examine the behavior of large charged droplets that contain analytes such as proteins or polymers, thereby providing insights into electrospray ionization (ESI) mechanisms. In the present study, we use this approach to investigate the release of polylactide (PLA) ions from water/acetonitrile ESI droplets. We found that cationized gaseous PLA ions can be formed via various competing pathways. Some MD runs showed extrusion and subsequent separation of polymer chains from the droplet, as envisioned by the chain ejection model (CEM). On other occasions the PLA chains remained inside the droplets and were released after solvent evaporation to dryness, consistent with the charge residue model (CRM). Following their release from ESI droplets, the nascent gaseous PLA ions were subjected to structural relaxation for several μs in vacuo. The MD conformations generated in this way for various PLA charge states compared favorably to experimental results obtained by ion mobility spectrometry-mass spectrometry (IMS-MS). The structures of all PLA ions evolved during relaxation in the gas phase. However, some macroion species retained features that resembled their nascent structures. For this subset of ions, the IMS-MS response appears to be strongly correlated with the ESI release mechanism (CEM vs. CRM). The former favored extended structures, whereas the latter preferentially generated compact conformers.
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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 | 0.001 |
| 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 | 0.001 |
| 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".