Modulation of Fe‐S cluster midpoint potential and electron transfer rates in <i>Escherichia coli</i> succinate dehydrogenase
Bibliographic record
Abstract
Succinate Dehydrogenase (Sdh, Complex II) is an indispensable enzyme involved in the Krebs cycle as well as energy coupling in the mitochondria and certain prokaryotes. During enzyme turnover, succinate is oxidized to fumarate in the catalytic subunit (SdhA) and donates two electrons to a flavin adenine dinucleotide cofactor. The electrons are then shuttled singly through a series of iron‐sulfur (Fe‐S) clusters in SdhB until they reach the membrane anchor domain (SdhCD), where they reduce ubiquinone to ubiquinol. At the heart of the electron transport chain is a [4Fe‐4S] cluster (FS2) with a low midpoint potential ( E o ) that acts as an energy barrier against electron transfer. Hydrophobic residues around FS2 were mutated to determine their effects on Fe‐S cluster electrochemistry as well as electron transfer rates. SdhB‐I150E and SdhB‐I150H mutants lowered the E o of FS2; surprisingly, the His variant had a lower E o than the Glu mutant. Mutation of SdhB‐L220 to His had no effect, but mutation to Asp lowered the E o of FS2. More interestingly, converting SdhB‐L220 to Ser did not alter the electrochemistry of FS2 but instead lowered the E o of the [3Fe‐4S] cluster. To corroborate the E o changes in these mutants to enzyme function, numerous assays were performed. These included aerobic growth in succinate minimal media, anaerobic growth in glycerol‐fumarate minimal media, non‐physiological succinate:PMS‐MTT enzyme assay, physiological succinate:Q 0 enzyme assay, and heme reduction assay. In general, it was discovered that a decrease in E o of either the [4Fe‐4S] cluster or the [3Fe‐4S] cluster is accompanied by a decrease in the rate of enzyme turnover. This research is funded by the AHFMR and CIHR.
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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".