Rates of Proton Transfer from Carboxylic Acids to Dianions, CO<sub>2</sub>(CH<sub>2</sub>)<i><sub>p</sub></i>CO<sub>2</sub><sup>2-</sup>, and Their Significance to Observed Negative Charge States of Proteins in the Gas Phase
Bibliographic record
Abstract
The carboxylic acid dianions, CO 2 (CH 2 ) p CO 2 2-, are the simplest model for two deprotonated acidic side chains, such as Glu or Asp, which are on opposite sides of a nondenatured globular protein. Rate constant determinations of the charge reducing reaction, CO 2 (CH 2 ) p CO 2 2- + AH = HCO 2 (CH 2 ) p CO 2 - + A -, involving dianions with C n where n ranges from 7 to 16 ( n = p + 2) with a variety of oxygen acids AH including acetic acid, show that charge reduction (loss) occurs at collision rates for all of the above reagents. This is in contrast with results for the positively charged proteins. Charge loss at collision rates in the model reaction (for two lysine side chains), NH 3 + H 3 N(CH 2 ) p NH 3 2+ = NH 3 (CH 2 ) p NH 2 + + NH 4 +, occurs only for C n when n < 7 ( n = p ). These results provide an explanation for the lower charged states of nondenatured proteins in the negative ion mode, relative to the positive ion mode, observed in the literature when the proteins are sprayed from aqueous solution with ammonium acetate buffer. According to the charge residue model (CRM), if an ammonium acetate buffer is used, charging of the protein will occur via NH 4 + in the positive ion mode and CH 3 CO 2 - in the negative ion mode. The much lower tolerance for proximity of another charge in proteins in the negative ion mode, revealed by the rate measurements of the dianions reacting with acetic acid, is due to the different effects of alkyl substitution on the intrinsic basicities in the positive ion mode and on the intrinsic acidities in the negative ion mode.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".