Thermostabilization, Expression, Purification, and Crystallization of the Human Serotonin Transporter Bound to <em>S</em>-citalopram
Bibliographic record
Abstract
The serotonin transporter is a sodium and chloride-coupled transporter that "pumps" extracellular serotonin into cells. S-citalopram is a drug used to treat depression and anxiety by binding to the serotonin transporter with high-affinity, blocking serotonin reuptake. Here we report an efficient procedure and a set of tools to stabilize, express, purify, and crystallize serotonin transporter-antibody complexes bound to S-citalopram and other antidepressants. Mutations which stabilize the serotonin transporter were identified using an S-citalopram binding assay. Serotonin transporter expressed in baculovirus-transduced HEK293S GnTI- cells, was reconstituted into proteoliposomes and used to raise high-affinity antibodies. We have developed a strategy to discover antibodies that are useful for structural studies. A straightforward approach for the expression of antibody fragments in Sf9 cells has also been established. Transporter-antibody complexes purified using this procedure are well-behaved and readily crystallize, producing complexes with S-citalopram that diffract X-rays to 3-4 Å resolution. The strategies developed here can be utilized to determine the structure of other challenging membrane proteins.
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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 | 0.001 |
| 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".