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Record W2413386661 · doi:10.1007/978-1-59745-205-2_6

Pharmacogenomics of G Protein-Coupled Receptor

2008· review· en· W2413386661 on OpenAlexaff
Miles D. Thompson, David E.C. Cole, Pedro A. José

Bibliographic record

VenueMethods in molecular biology · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPharmacogenomicsPharmacologyMedicineComputational biologyBiology

Abstract

fetched live from OpenAlex

The identification and characterization of the processes of G protein-coupled receptor (GPCR) activation and inactivation have refined not only the study of the GPCRs but also the genomics of many accessory proteins necessary for these processes. This has accelerated progress in understanding the fundamental mechanisms involved in GPCR structure and function, including receptor transport to the membrane, ligand binding, activation and inactivation by GRK-mediated (and other) phosphorylation. The catalog of G(s)alpha and Gbeta subunit polymorphisms that result in complex phenotypes has complemented the effort to catalog the GPCRs and their variants. The study of the genomics of GPCR accessory proteins has also provided insight into pathways of disease, such as the contributions of regulator of G protein signaling (RGS) protein to hypertension and activator of G protein signaling (AGS) proteins to the response to hypoxia. In the case of the G protein-coupled receptor kinases (GRKs), identified originally in the retinal tissues that converge on rhodopsin, proteins such as GRK4 have been identified that have been subsequently associated with hypertension. Here, we review the structure and function of GPCR and associated proteins in the context of the gene families that encode them and the genetic disorders associated with their altered function. An understanding of the pharmacogenomics of GPCR signaling provides the basis for examining the GPCRs disrupted in monogenic disease and the pharmacogenetics of a given receptor system.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.722
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.044
GPT teacher head0.423
Teacher spread0.379 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreReview

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".

Quick stats

Citations43
Published2008
Admission routes1
Has abstractyes

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