Common and selective signal transduction mechanisms of GPCRs
G protein-coupled receptors (GPCRs) are coupled by four major subfamilies of G proteins. GPCR coupling is processed through a combination of common and selective activation mechanisms together. Common mechanisms are shared for a group of receptors. Recently, researchers managed to identify shared activation pathways for the GPCRs belonging to the same subfamilies. On the other hand, selective mechanisms are responsible for the variations within activation mechanisms. Selective processes can regulate subfamily-specific interactions between the receptor and the G proteins, and intermediate receptor conformations are required to couple particular G proteins through G protein-specific activation mechanisms.
Moreover, G proteins can also selectively interact with RGS (regulators of G protein signaling) proteins as well. Selective processes modulate the signaling profile of the receptor and the tissue they are present. This chapter summarizes the recent research conducted on common and selective signal transduction mechanisms within GPCRs from an evolutionary perspective.
- Sibling rivalry among the ZBTB transcription factor family: homodimers versus heterodimers
- PHACT: Phylogeny-Aware Computing of Tolerance for Missense Mutations
- Evolutionary association of receptor-wide amino acids with G protein-coupling selectivity in aminergic GPCRs
- Phylostat: a web-based tool to analyze paralogous clade divergence in phylogenetic trees
- The mutation profile of SARS-CoV-2 is primarily shaped by the host antiviral defense
- The utility of next-generation sequencing technologies in diagnosis of Mendelian mitochondrial diseases and reflections on clinical spectrum
- Phylogenetic analysis of SARS-CoV-2 genomes in Turkey
- Class III histidine kinases: a recently accessorized kinase domain in putative modulators of type IV pili based motility.
- Cache domains are dominant extracellular sensors for signal transduction in prokaryotes.
- Establishing the precise evolutionary history of a gene improves predicting disease-causing missense mutations.