On the Mechanism of Cytoprotection by Ferrostatin-1 and Liproxstatin-1 and the Role of Lipid Peroxidation in Ferroptotic Cell Death
Bibliographic record
Abstract
Ferroptosis is a form of regulated necrosis associated with the iron-dependent accumulation of lipid hydroperoxides that may play a key role in the pathogenesis of degenerative diseases in which lipid peroxidation has been implicated. High-throughput screening efforts have identified ferrostatin-1 (Fer-1) and liproxstatin-1 (Lip-1) as potent inhibitors of ferroptosis - an activity that has been ascribed to their ability to slow the accumulation of lipid hydroperoxides. Herein we demonstrate that this activity likely derives from their reactivity as radical-trapping antioxidants (RTAs) rather than their potency as inhibitors of lipoxygenases. Although inhibited autoxidations of styrene revealed that Fer-1 and Lip-1 react roughly 10-fold more slowly with peroxyl radicals than reactions of α-tocopherol (α-TOH), they were significantly more reactive than α-TOH in phosphatidylcholine lipid bilayers - consistent with the greater potency of Fer-1 and Lip-1 relative to α-TOH as inhibitors of ferroptosis. None of Fer-1, Lip-1, and α-TOH inhibited human 15-lipoxygenase-1 (15-LOX-1) overexpressed in HEK-293 cells when assayed at concentrations where they inhibited ferroptosis. These results stand in stark contrast to those obtained with a known 15-LOX-1 inhibitor (PD146176), which was able to inhibit the enzyme at concentrations where it was effective in inhibiting ferroptosis. Given the likelihood that Fer-1 and Lip-1 subvert ferroptosis by inhibiting lipid peroxidation as RTAs, we evaluated the antiferroptotic potential of 1,8-tetrahydronaphthyridinols (hereafter THNs): rationally designed radical-trapping antioxidants of unparalleled reactivity. We show for the first time that the inherent reactivity of the THNs translates to cell culture, where lipophilic THNs were similarly effective to Fer-1 and Lip-1 at subverting ferroptosis induced by either pharmacological or genetic inhibition of the hydroperoxide-detoxifying enzyme Gpx4 in mouse fibroblasts, and glutamate-induced death of mouse hippocampal cells. These results demonstrate that potent RTAs subvert ferroptosis and suggest that lipid peroxidation (autoxidation) may play a central role in the process.
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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 | 0.000 |
| 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 | 0.000 |
| 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".