cd14964: 7tm_GPCRs (this model, PSSM-Id:320095 is obsolete and has been replaced by 410628)
seven-transmembrane G protein-coupled receptor superfamily
This hierarchical evolutionary model represents the seven-transmembrane (7TM) receptors, often referred to as G protein-coupled receptors (GPCRs), which transmit physiological signals from the outside of the cell to the inside via G proteins. GPCRs constitute the largest known superfamily of transmembrane receptors across the three kingdoms of life that respond to a wide variety of extracellular stimuli including peptides, lipids, neurotransmitters, amino acids, hormones, and sensory stimuli such as light, smell and taste. All GPCRs share a common structural architecture comprising of seven-transmembrane (TM) alpha-helices interconnected by three extracellular and three intracellular loops. A general feature of GPCR signaling is agonist-induced conformational changes in the receptors, leading to activation of the heterotrimeric G proteins, which consist of the guanine nucleotide-binding G-alpha subunit and the dimeric G-beta-gamma subunits. The activated G proteins then bind to and activate numerous downstream effector proteins, which generate second messengers that mediate a broad range of cellular and physiological processes. However, some 7TM receptors, such as the type 1 microbial rhodopsins, do not activate G proteins. Based on sequence similarity, GPCRs can be divided into six major classes: class A (the rhodopsin-like family), class B (the Methuselah-like, adhesion and secretin-like receptor family), class C (the metabotropic glutamate receptor family), class D (the fungal mating pheromone receptors), class E (the cAMP receptor family), and class F (the frizzled/smoothened receptor family). Nearly 800 human GPCR genes have been identified and are involved essentially in all major physiological processes. Approximately 40% of clinically marketed drugs mediate their effects through modulation of GPCR function for the treatment of a variety of human diseases including bacterial infections.
Jiyao W et al.(2023). "The conserved domain database in 2023.",