The proteins in the GPCRDB are collected by mining NCBI's NR database for GPCRs. We use hidden Markov models (HMMs) to classify the proteins.
The alignments in the GPCRDB are created by using position-specific profiles. The use of such profiles allows for high-quality alignments. For each protein family the protein sequences of the classified proteins are aligned by the WhatIf software package as described in
Currently we have two different repositories, the MuteXt repository and the tinyGRAP database. The mutations from MuteXt were automatically extracted from literature, whereas the tinyGRAP mutants were extracted hand. The tinyGRAP data is very extensive and the GPCRDB offers only a small part of the functionality the tinyGPAP website offers. For more search power we advice you to take a look there.
Ligand binding data
We have a number of different sources of ligand binding data. There is data from the StarLite database, datasets from Organon (now Shering-Plough) and data provided by P. Seeman.
For information about the StarLite data, please look here.
For information about the organon data, please look here.
The Seeman ligand binding data has kindly been made available by P. Seeman:
Seeman P. (1993) Receptor Tables, vol.2: Drug dissociation constants for neuroreceptors and transporters. Toronto: SZ Research.
The GPCRDB currently contains:
|Ligand binding experiments||2648|
You can download the protein family members and class descriptions:
The database schema can be downloaded here.