A single-nucleotide polymorphism of alanine to threonine at position 163 of the human angiotensin II type 1 receptor impairs Losartan affinity
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: AT1 is the principal receptor for angiotensin II (AngII), which regulates blood pressure and osmotic homeostasis. Earlier studies have shown that position 163 interacts with the antihypertensive nonpeptide antagonist, Losartan. A recently discovered polymorphism found in humans (rs12721226) coding for residue 163 led us to determine whether this polymorphism would affect Losartan antihypertensive therapies. The pharmacological properties of the A163T hAT1 variant are described. METHOD AND RESULTS: The A163T hAT1 mutation was evaluated by testing its affinity by dose displacement of AngII analogs in COS-7 cells expressing either wild-type hAT1 or the A163T hAT1. The expressions of the receptors were evaluated by saturation binding and the efficacies were assessed by measuring the 3H-inositol phosphate production. The results showed that the A163T hAT1 receptor is comparable with the affinity, expression, and efficacy of native hAT1 towards peptide ligands. The affinities were also tested with nonpeptide antagonists Losartan, L-158 809, valsartan, telmisartan, irbesartan, candesartan, and EXP3174. Losartan and EXP3174 displayed a 7-fold loss in affinity towards A163T hAT1. The ability of Losartan to inhibit AngII-induced inositol triphosphate production also confirmed a loss in efficacy. Molecular modeling showed a higher steric and hydrophilic hindrance of the A163T hAT1-Losartan complex. CONCLUSION: The polymorphism that codes for the A163T hAT1 variant results in a receptor with normal physiological properties toward the endogenous hormone. However, the significant reduction in affinity to Losartan and its active metabolite, EXP3174, could significantly impair the clinical effectiveness of an antihypertensive therapy using Losartan with patients bearing the A163T polymorphism.
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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) | 0.001 | 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) | 0.004 | 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".