Computational methods for studying G protein-coupled receptors (GPCRs).

The functioning of GPCRs is classically described by the ternary complex model as the interplay of three basic components: a receptor, an agonist, and a G protein. According to this model, receptor activation results from an interaction with an agonist, which translates into the activation of a particular G protein in the intracellular compartment that, in turn, is able to initiate particular signaling cascades. Extensive studies on GPCRs have led to new findings which open unexplored and exciting possibilities for drug design and safer and more effective treatments with GPCR targeting drugs. These include discovery of novel signaling mechanisms such as ligand promiscuity resulting in multitarget ligands and signaling cross-talks, allosteric modulation, biased agonism, and formation of receptor homo- and heterodimers and oligomers which can be efficiently studied with computational methods. Computer-aided drug design techniques can reduce the cost of drug development by up to 50%. In particular structure- and ligand-based virtual screening techniques are a valuable tool for identifying new leads and have been shown to be especially efficient for GPCRs in comparison to water-soluble proteins. Modern computer-aided approaches can be helpful for the discovery of compounds with designed affinity profiles. Furthermore, homology modeling facilitated by a growing number of available templates as well as molecular docking supported by sophisticated techniques of molecular dynamics and quantitative structure-activity relationship models are an excellent source of information about drug-receptor interactions at the molecular level.