On the substrate turnover rate of NBCe1 and AE1 SLC4 transporters: structure-function considerations
Bibliographic record
Abstract
A transport protein’s turnover rate (TOR) is the maximum rate of substrate translocation under saturating conditions. This parameter represents the number of transporting events per transporter molecule (assuming a single transport site) per second (s). From this standpoint, a transporter’s TOR is similar to an enzyme’s catalytic constant. Knowledge of a transporter’s TOR allows comparison of the transport capacity of various transporters at the molecular level as well as the total transport per cell and whole organ levels. Despite this, there is currently a very limited number of transporters, for which TOR has been determined experimentally. In the SLC4 transporter family of CO32−/HCO3− transporters, erythrocyte AE1 (eAE1; SLC4A1) is the only member, for which TOR has been determined (∼50,000 s−1). Whether other SLC4 family members have similar TOR values is currently unknown. Here we report TOR measurements of the electrogenic Na+-CO32− cotransporter NBCe1-A (SLC4A4) and the kidney specific AE1 splice variant, kAE1, that play important roles in renal bicarbonate absorption and are mutated in proximal and distal renal tubular acidosis respectively. We have also remeasured the eAE1 TOR value for comparison. NBCe1-A had a TOR value of ∼30,400 s−1 whereas kAE1 and eAE1 had significantly higher values (62,000 s−1 and 60,500 s−1 respectively). We modeled the inward-facing (IF) conformation of NBCe1-A to determine conformational changes during its transport cycle. Comparison of this IF model with our previously determined cryoelectron microscopy (cryoEM) outward-facing (OF) conformation structure, demonstrates that NBCe1-A has an elevator-type transport mechanism with a small vertical ∼5 Å shift of the ion coordination site as we have previously shown for AE1. We speculate that this very small vertical movement plays an important role in contributing to the very high TOR numbers of SLC4 transporters.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".