Heat-Induced Protein Oxidation as an Impediment for Thermal Stability Measurements: A Case Study on Cytochrome <i>c</i>
Bibliographic record
Abstract
Thermal unfolding (“melting”) experiments are widely used for protein stability measurements. These assays probe spectroscopic properties of the protein while gradually increasing the solution temperature until unfolding is complete. Thermodynamic parameters are obtained from fits of the resulting profiles. Differential scanning calorimetry relies on similar concepts. Meaningful stability measurements require reversible conditions, where the protein fluctuates between its native and unfolded states (N ⇌ U), as governed by the temperature-dependent equilibrium constant. A simple reversibility test is to ensure that heating and cooling (unfolding and refolding) profiles are superimposable. Unfortunately, such tests are not commonly performed. Here, we focused on cytochrome c, one of the most widely used model proteins for folding studies. Surprisingly, thermal unfolding/refolding was found to be irreversible, even in the absence of aggregation. Using mass spectrometry (MS), we traced the origin of this irreversibility to oxidative side chain modifications that accumulate during thermal assays. By gradually altering the covalent composition of the protein, oxidation creates a scenario far from ideal N ⇌ U conditions, rendering the validity of fitted thermodynamic parameters questionable. Oxidation at Tyr, Trp, and Met residues was promoted by dissolved O 2 . It appears that the role of oxidation as an impediment for protein stability assays has been overlooked in the past. While the use of deoxygenated solutions represents a partial remedy, it is hoped that better oxidation suppression strategies will be developed in the future. In any case, it is advisable to perform MS measurements alongside thermal protein stability experiments to ensure that problems related to oxidation-mediated irreversibility are properly recognized.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".