G Protein-Coupled Receptor Pharmacogenetics
Bibliographic record
Abstract
Common G protein-coupled receptor (GPCR) gene variants that encode receptor proteins with a distinct sequence may alter drug efficacy without always resulting in a disease phenotype. GPCR genetic loci harbor numerous variants, such as DNA insertions or deletions and single-nucleotide polymorphisms that alter GPCR expression and function, thereby contributing to interindividual differences in disease susceptibility/progression and drug responses. In this chapter, these pharmacogenetic phenomena are reviewed with respect to a limited sampling of GPCR systems, including the beta(2)-adrenergic receptors, the cysteinyl leukotriene receptors, and the calcium-sensing receptor. In each example, the nature of the disruption to receptor function that results from each variant is discussed with respect to the regulation of gene expression, expression on cell surface (affected by receptor trafficking, dimerization, desensitization/downregulation), or perturbation of receptor function (by altering ligand binding, G protein coupling, and receptor constitutive activity). Despite the breadth of pharmacogenetic knowledge available, assessment for genetic variants is only occasionally applied to drug development projects involving pharmacogenomics or to optimizing the clinical use of GPCR drugs. The continued effort by the basic science of pharmacogenetics may draw the attention of drug discovery projects and clinicians alike to the utility of personalized pharmacogenomics as a means to optimize novel GPCR drug targets.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.002 | 0.001 |
| 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".