Thermostabilization of the Human Serotonin Transporter in an Antidepressant-Bound Conformation
Bibliographic record
Abstract
Serotonin is a ubiquitous chemical transmitter with particularly important roles in the gastrointestinal, cardiovascular and central nervous systems. Modulation of serotonergic signaling occurs, in part, by uptake of the transmitter by the serotonin transporter (SERT). In the brain, SERT is the target for numerous antidepressants including tricyclic antidepressants and selective serotonin reuptake inhibitors (SSRIs). Despite the importance of SERT in human physiology, biochemical, biophysical and high-resolution structural studies have been hampered due to the instability of SERT in detergent micelles. To identify a human SERT (hSERT) construct suitable for detailed biochemical and structural studies, we developed an efficient thermostability screening protocol and rapidly screened 219 mutations for thermostabilization of hSERT in complex with the SSRI paroxetine. We discovered three mutations-Y110A, I291A and T439S -that, when combined into a single construct, deemed TS3, yielded a hSERT variant with an apparent melting temperature (Tm) 19°C greater than that of the wild-type transporter, albeit with a loss of transport activity. Further investigation yielded a double mutant-I291A and T439S-defined as TS2, with a 12°C increase in Tm and retention of robust transport activity. Both TS2 and TS3 were more stable in short-chain detergents in comparison to the wild-type transporter. This thermostability screening protocol, as well as the specific hSERT variants, will prove useful in studies of other integral membrane receptors and transporters and in the investigation of structure and function relationships in hSERT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".