Characterizing pharmacological ligands to study the long‐chain fatty acid receptors <scp>GPR</scp>40/<scp>FFA</scp>1 and <scp>GPR</scp>120/<scp>FFA</scp>4
Bibliographic record
Abstract
The free fatty acid receptors (FFA) 1 (previously designated GPR40) and FFA4 (previously GPR120) are two GPCRs activated by saturated and unsaturated longer-chain free fatty acids. With expression patterns and functions anticipated to directly or indirectly promote insulin secretion, provide homeostatic control of blood glucose and improve tissue insulin sensitivity, both receptors are being studied as potential therapeutic targets for the control of type 2 diabetes. Furthermore, genetic and systems biology studies in both humans and mouse models link FFA4 receptors to diabetes and obesity. Although activated by the same group of free fatty acids, FFA1 and FFA4 receptors are not closely related and, while the basis of recognition of fatty acids by FFA1 receptors is similar to that of the short-chain fatty acid receptors FFA2 and FFA3, the amino acid residues involved in endogenous ligand recognition by FFA4 receptors are more akin to those of the sphingosine 1 phosphate receptor S1P1 . Screening and subsequent medicinal chemistry programmes have developed a number of FFA1 receptor selective agonists that are effective in promoting insulin secretion in a glucose concentration-dependent manner, and in lowering blood glucose levels. However, the recent termination of Phase III clinical trials employing TAK-875/fasiglifam has caused a setback and raises important questions over the exact nature and mechanistic causes of the problems. Progress in the identification and development of highly FFA4 receptor-selective pharmacological tools has been less rapid and several issues remain to be clarified to fully validate this receptor as a therapeutic target. Despite this, the ongoing development of a range of novel ligands offers great opportunities to further unravel the contributions of these receptors.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".