4-(4-(Dimethylamino)phenyl)-1-methylpyridinium (APP+) Is a Fluorescent Substrate for the Human Serotonin Transporter
Bibliographic record
Abstract
Monoamine transporters terminate synaptic neurotransmission and are molecular targets for antidepressants and psychostimulants. Fluorescent reporters can monitor real-time transport and are amenable for high-throughput screening. However, until now, their use has mostly been successful to study the catecholamine transporters but not the serotonin (5HT) transporter. Here, we use fluorescence microscopy, electrophysiology, pharmacology, and molecular modeling to compare fluorescent analogs of 1-methyl-4-phenylpyridinium (MPP(+)) as reporters for the human serotonin transporter (hSERT) in single cells. The fluorescent substrate 4-(4-(dimethylamino)phenyl)-1-methylpyridinium (APP(+)) exhibits superior fluorescence uptake in hSERT-expressing HEK293 cells than other MPP(+) analogs tested. APP(+) uptake is Na(+)- and Cl(-)-dependent, displaced by 5HT, and inhibited by fluoxetine, suggesting APP(+) specifically monitors hSERT activity. ASP(+), which was previously used to study catecholamine transporters, is 10 times less potent than APP(+) at inhibiting 5HT uptake and has minimal hSERT-mediated uptake. Furthermore, in hSERT-expressing oocytes voltage-clamped to -60 mV, APP(+) induced fluoxetine-sensitive hSERT-mediated inward currents, indicating APP(+) is a substrate, whereas ASP(+) induced hSERT-mediated outward currents and counteracted 5HT-induced hSERT currents, indicating ASP(+) possesses activity as an inhibitor. Extra-precise ligand receptor docking of APP(+) and ASP(+) in an hSERT homology model showed both ASP(+) and APP(+) docked favorably within the active region; accordingly, comparable concentrations are required to elicit their opposite electrophysiological responses. We conclude APP(+) is better suited than ASP(+) to study hSERT transport fluorometrically.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".