GPCR-PEnDB: a database of protein sequences and derived features to facilitate prediction and classification of G protein-coupled receptors

Abstract

G protein-coupled receptors (GPCRs) constitute the largest group of membrane receptor proteins in eukaryotes. Due to their significant roles in various physiological processes such as vision, smell and inflammation, GPCRs are the targets of many prescription drugs. However, the functional and sequence diversity of GPCRs has kept their prediction and classification based on amino acid sequence data as a challenging bioinformatics problem. There are existing computational approaches, mainly using machine learning and statistical methods, to predict and classify GPCRs based on amino acid sequence and sequence derived features. In this paper, we describe a searchable MySQL database, named GPCR-PEnDB (GPCR Prediction Ensemble Database), of confirmed GPCRs and non-GPCRs. It was constructed with the goal of allowing users to conveniently access useful information of GPCRs in a wide range of organisms and to compile reliable training and testing datasets for different combinations of computational tools. This database currently contains 3129 confirmed GPCR and 3575 non-GPCR sequences collected from the UniProtKB/Swiss-Prot protein database, encompassing over 1200 species. The non-GPCR entries include transmembrane proteins for evaluating various prediction programs' abilities to distinguish GPCRs from other transmembrane proteins. Each protein is linked to information about its source organism, classification, sequence lengths and composition, and other derived sequence features. We present examples of using this database along with its graphical user interface, to query for GPCRs with specific sequence properties and to compare the accuracies of five tools for GPCR prediction. This initial version of GPCR-PEnDB will provide a framework for future extensions to include additional sequence and feature data to facilitate the design and assessment of software tools and experimental studies to help understand the functional roles of GPCRs. Database URL: gpcr.utep.edu/database.

Figure 1.

Different regions of a typical GPCR molecule. GPCR consists of a single polypeptide chain of amino acids folded into seven transmembrane helices (TMH1–7) between an extracellular N-terminal and an intracellular C-terminal. The seven transmembrane helices are connected by three extracellular loops (ECL1–3) and three intracellular loops (ICL1–3).

Figure 5.

Web interface of GPCR-PEnDB, showing both Quick Search (top) and Advanced Search options (bottom).

Figure 2.

G protein-coupled receptor Prediction Ensemble Database (GPCR-PEnDB) overview showing the tables in the database, number of sequence entries, available web-server search options, and different types of algorithms for GPCR prediction and classification.

Figure 3.

Number of sequences in different groups of organisms in the GPCR datasets. Groups with more than 40 sequences are shown as separate bars. The remaining ones are grouped as “Others”.

Figure 4.

MySQL query asking for GPCRs in Class A with more than 10% serine and C-terminal longer than 300 amino acid residues.

Figure 6.

Results table from the search of GPCR sequences longer than 3000 amino acids using the web server. The table entries can be downloaded in CSV format by clicking on the “Result table” link, and the corresponding protein sequences can be downloaded in FASTA format by clicking on the “FASTA file” link.