A Glutamine to Glutamate Mutation at Position 170 (Q170E) in the Rabbit Na<sup>+</sup>/Glucose Cotransporter, rSGLT1, Enhances Binding Affinity for Na<sup>+</sup>
Bibliographic record
Abstract
Using cysteine mutagenesis and chemical modification by methanethiosulfonate derivatives, it was demonstrated that the external putative loop, joining transmembrane segments (TM's) IV-V of rabbit Na+/glucose cotransporter, rSGLT1, forms part of a Na+ binding and voltage sensing domain. Within this region, exposure to cationic (2-aminoethyl)methanethiosulfonate hydrobromide (MTSEA) inhibited F163C, A166C, and L173C, but anionic sodium (2-sulfonatoethyl)methanethiosulfonate (MTSES) had no effect. Unexpectedly, MTSEA had no effect on Q170C; however, MTSES profoundly altered Q170C charge transfer and turnover, leaving Na+ and sugar binding affinity unchanged, but mutation of glutamine to anionic glutamate (Q170E) shifted V(0.5) to positive potentials, suggesting enhanced Na+ affinity. To clarify the role of glutamine 170 in Na+ interaction, we embarked on a more detailed investigation of Q170E using the two-microelectrode voltage clamping in Xenopus oocytes. Compared to wild-type (wt) rSGLT1, Q170E exhibits (i) a 2-fold decrease in methyl alpha-D-glucopyranoside affinity (-150 to -90 mV), (ii) a 5-fold increase in Na+ affinity (-150 to -100 mV) with less voltage dependency, (iii) reduced Na+ leak, and (iv) two transient current decay constants (tau(fast), tau(slow)) compared to three (tau(fast), tau(medium), tau(slow)) for wt, and computer simulation of Q170E pre-steady-state currents with a four-state kinetic model yields parameters similar to wt SGLT1, except for a reduced Na+ debinding rate constant compared to wt. Taken together, the data strengthen the conclusion that residue 170 lies in the Na+ pathway and provide the first evidence that it participates in determining Na+ binding.
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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 | 0.001 |
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".