An overview of recent developments in GPCR modelling: methods and validation

The use of G-protein coupled receptor models in lead optimization

With the emerging new crystal structures of G-protein coupled receptors (GPCRs), the number of reported in silico receptor models vastly increases every year. The use of these models in lead optimization (LO) is investigated here. Although there are many studies where GPCR models are used to identify new chemotypes by virtual screening, the classical application in LO is rarely reported. The reason for this may be that the quality of a model, which is appropriate for atomistic modeling, must be very high, and the biology of GPCR ligand-dependent signaling is still not fully understood. However, the few reported studies show that GPCR models can be used efficiently in LO for various problems, such as affinity optimization or tuning of physicochemical parameters.

G-protein-coupled receptor-focused drug discovery using a target class platform approach

In recent years, several large pharmaceutical companies have taken a novel approach to drug discovery biology and chemistry in that they channel their efforts with respect to particular target classes, such as G-protein-coupled receptors (GPCRs), toward dedicated, specialized teams. Benefits of such an organizational structure are the prospects of establishing several target-family-specific experimental techniques and skill sets, thereby enabling a comprehensive functional profiling of drug candidates in different pharmacological respects. In this context, the recently increased number of reports on GPCR ligand-biased signaling has further spurred the efforts in the pharmaceutical industry toward broader biological characterization of the test compounds, for example employing high-content screening to analyze different GPCR ligand-induced signaling pathways. The knowledge of the disease-relevant functional properties of the small molecule GPCR ligands enables target-specific chemical optimization and GPCR-subclass-directed library design. In the case of GPCRs, where little--although at present slowly expanding--structural information on the targets is available, the modeling of GPCR structures crucially depends on biological validation (typically supported by site-directed mutagenesis of the GPCR ligand binding site). In this review, we aim to recapitulate efforts in the pharmaceutical industry to address GPCR-directed drug discovery in a target-class-directed platform approach: establishing GPCR-specific biological assay panels and creating computational chemistry methods for finding and optimizing small molecules modulating the activity of GPCRs.

Molecular modeling of A1 and A2A adenosine receptors: comparison of rhodopsin- and beta2-adrenergic-based homology models through the docking studies

Adenosine receptors (ARs) are members of the superfamily of G protein-coupled receptors. The homology models of adenosine A1 and A2A receptors were constructed. The high-resolution X-ray structure of bovine rhodopsin and crystal structure of beta2-adrenergic receptor were used as templates. The binding sites of the A1 and A2A ARs were constructed by using data obtained from mutagenesis experiments as well as docking simulations of the respective AR antagonsists DPCPX and XAC. To compare rhodopsin- and beta2-adrenergic-based models, the binding mode of A1 (KW-3902, LUF-5437) and A2A (KW-6002, ZM-241385) ARs antagonists were also examined. The differences in the binding ability of both models were noted during the study. The beta2-adrenergic-based A2A AR model was much more capable to stabilize the ligand in the binding site cavity than the corresponding rhodopsin-based A2A AR model, however, such differences were not so clear in case of A1 AR models. It was suggested that for the A1 AR it is possible to use the crystal structure of rhodopsin as a template as well as beta2-adrenergic receptor, but for A2A AR, with the now available beta2-adrenergic receptor X-ray structure, docking studies should be avoided on the rhodopsin-based model. However, taking into account that the beta2AR shares about 31% of the residues with the AR in comparison to 21% in case of bRho, we suggest using beta2-adrenergic-based models for the A1 and A2A ARs for further in silico ligand screening also because of their generally better ability to stabilize ligands inside the binding pocket.

Molecular modeling of adenosine receptors: new results and trends

Adenosine is a ubiquitous neuromodulator, which carries out its biological task by stimulating four cell surface receptors (A(1), A(2A), A(2B), and A(3)). Adenosine receptors (ARs) are members of the superfamily of G protein-coupled receptors (GPCRs). Their discovery opened up new avenues for potential drug treatment of a variety of conditions such as asthma, neurodegenerative disorders, chronic inflammatory diseases, and many other physiopathological states that are believed to be associated with changes in adenosine levels. Knowledge of the 3D structure of ARs could be of great help in the task of understanding their function and in the rational design of specific ligands. However, since GPCRs are membrane-bound proteins, high-resolution structural characterization is still an extremely difficult task. For this reason, great importance has been placed on molecular modeling studies and, particularly in the last few years, on homology modeling (HM) techniques. The publication of the first high-resolution crystal structure for bovine rhodopsin (bRh), a GPCR superfamily member, provides the option of utilizing HM to generate 3D models based on detailed structural information. In this review we report, analyze, and compare the main experimental data, computational HM procedures and validation methods used for ARs, describing in detail the most successful results.