Identification of residues in human melatonin type 2 receptor involved in signaling selectivity or general signal transmission using natural variants
Bibliographic record
Abstract
Melatonin is a neurohormone secreted by the pineal gland mainly regulating circadian rhythm and binding to 2 receptors: MT 1 and MT 2 . A recent genome‐wide association studies revealed 40 non‐synonymous polymorphisms of MT 2 . All these variants are normally expressed at cell surface and 4 of them show loss of melatonin binding. Given that no crystal structure is available yet for MT 2 and that variants are well distributed along MT 2 , we took advantage of these natural variants to delineate structural features controlling MT 2 functionality. By monitoring β‐arrestin 2 recruitment, ERK phosphorylation, inhibition of cAMP production, Gα i1 and Gα z activation, we generated 40 signaling signatures and similar profiles were grouped together using non‐negative matrix factorization (NMF). A total of 8 different types of signatures (clusters) were obtained. Each cluster has unique signaling features and is distinctly spatially localized along MT 2 . While residues important for general signal transmission are located in transmembrane regions, the residues responsible for signal selectivity are almost exclusively localized in intracellular domains. Using computational homology modeling (PDB ID: 4Zwj and 3sn6), we proposed molecular mechanisms underlying general signal transmission but also Gα/β‐arrestin and Gα z /Gα i1 selectivities. Altogether, our findings represent a proof of principle that natural variants of a given receptor can be exploited and used as a platform to learn more about its structural properties. Support or Funding Information This work was supported by a grant from FRQS to MB, from FRM and ANR to RJ and from NIH, NSF and DARPA to OL. Postdoctoral fellowships from CIHR and from Diabetes Canada to BP, from FRM to AK and from ETH Zurich to TF also funded this work. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0.001 |
| 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 | 0.000 |
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 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".