Updated on: January 7, 2020
GPCR-EXP is a database that specializes in curating experimental and predicted structures of G protein-coupled receptors (GPCR). Structure-related data for experimental structures, such as resolution, publication information, and biological ligand, from the Protein Databank (PDB) are extracted and incorporated into the database. Additionally, all GPCRs from the human genome have been modelled using GPCR-I-TASSER and have been included.
Easy-to-read tables have been constructed to faciliate the browsing of:
Furthermore, database statistics can be accessed to provide a glimpse into the current state of GPCR structural biology, while all PDB structures and data are freely available for download.
November 15, 2019
Apologies for the lack of updates for the past month, as we were undergoing cluster maintenance.
November 6, 2018
UniProt function annotations, including free text annotations and Gene Ontology (GO) terms, are now available for experimentally solved and computationally predicted GPCR structures. GO terms general to all GPCRs are excluded.
August 3, 2018
Binding site predictions from COACH are now available for all predicted GPCR structures.
June 15, 2018
'About' and 'Statistics' pages have been updated.
June 12, 2018
Predicted GPCR structures from the human genome have been added. Accessible from the 'Browse' tab.
June 11, 2018
Layout of database has been completely redesigned again. Each section can be accessed by clicking the tabs.
June 3, 2018
Additional data (structure overlays, ligands, PDB downloads, etc.) accessible by clicking buttons for a popup window on the browse page.
May 12, 2017
GPCR-EXP has been completely redesigned. GPCRs are now browsable in table form.
G protein-coupled receptors (GPCR) are an important superfamily of receptors that are involved in a plethora of physiological functions. Perhaps not surprisingly, they have been implicated in many diseases, such as cancer and diabetes. Having the 3D structure of these receptors plays an enormous role in elucidating its function and medical relevance, as well as facilitating structure-based drug design. In order to address this need, GPCR-EXP database is developed to comprehensively collects and curates data about all known GPCR structures.
GPCR-EXP is designed primarily to be browsed by the user and is organized into two major areas: 1. Experimental PDB structures, and 2. Predicted Structures for the Human Genome. GPCRs are stratified into Class A, Class B, Class C, and Class F for both areas, while predicted structures have the additional categories of 'Other' and 'Putative'. 'Other' GPCRS are experimentally verified but do not belong in the other classes, and 'Putative' GPCRs are those that have not yet been experimentally validated. GPCR structures can be browsed by class. Furthermore, users have the option to browse all structures for either major area all at once in one table.
Data for experimental structures are grouped by GPCR if browsing by class. For example, all available PDB structures for the 5-hydroxytryptamine receptor 1B are lumped into the same table. As shown in Figure 1, each PDB structure is represented by one row, where general information is given in each column. The user can view pre-superposed structures by clicking on 'Overlay Structures'. Clicking on 'Display Ligands' will allow the user to view all applicable pharmacological ligands for the structures of the GPCR, whiel clicking on 'Download Structures' provides a customizable download of PDB files. Clicking on the image of the GPCR structure will lead to additional structural and functional data about the PDB structure. Lastly, single PDB files can be downloaded from the table of either original structure, single chain structure, or ligand.
Data for predicted structures are grouped by sub-class for Class A GPCRs but grouped together for the other classes. Figure 2 shows a a grouping of the Class A Acetylcholine receptors, where each row represents a GPCR. General information, such as name and prediction statistics, are given in the columns. The user can click on 'Detailed Data' to access a more comprehensive results page generated by GPCR-I-TASSER.
Wallace Chan, Chengxin Zhang, Mohamed Said, S.M. Mortuza, Yang Zhang. GPCR-EXP: A semi-manually curated database for experimentally-solved and predicted GPCR structures. (2018) In preparation.
