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Modeling G Protein-Coupled Receptors: a Concrete Possibility.

ABSTRACT: G protein-coupled receptors (GPCRs) are a large superfamily of membrane bound signaling proteins that are involved in the regulation of a wide range of physiological functions and constitute the most common target for therapeutic intervention. Due to the paucity of crystal structures, homology modeling has become a widespread technique for the construction of GPCR models, which have been applied to the study of their structure-function relationships and to the identification of lead ligands through virtual screening. Rhodopsin has been for years the only available template. However, recent breakthroughs in GPCR crystallography have led to the solution of the structures of a few additional receptors. In light of these newly elucidated crystal structures, we have been able to produce a substantial amount of data to demonstrate that accurate models of GPCRs in complex with their ligands can be constructed through homology modeling followed by fully flexible molecular docking. These results have been confirmed by our success in the first blind assessment of GPCR modeling and docking, organized in coordination with the solution of the X-ray structure of the adenosine A(2A) receptor. Taken together, these data indicate that: a) the transmembrane helical bundle can be modeled with considerable accuracy; b) predicting the binding mode of a ligand, although doable, is challenging; c) modeling of the extracellular and intracellular loops is still problematic.

SUBMITTER: Costanzi S

PROVIDER: S-EPMC3022441 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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Modeling G Protein-Coupled Receptors: a Concrete Possibility.

Costanzi Stefano S

Chimica oggi 20100101 3

G protein-coupled receptors (GPCRs) are a large superfamily of membrane bound signaling proteins that are involved in the regulation of a wide range of physiological functions and constitute the most common target for therapeutic intervention. Due to the paucity of crystal structures, homology modeling has become a widespread technique for the construction of GPCR models, which have been applied to the study of their structure-function relationships and to the identification of lead ligands thro ...[more]

PMID: 21253444

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Project description:G protein-coupled receptors (GPCRs), encoded by about 5% of human genes, comprise the largest family of integral membrane proteins and act as cell surface receptors responsible for the transduction of endogenous signal into a cellular response. Although tertiary structural information is crucial for function annotation and drug design, there are few experimentally determined GPCR structures. To address this issue, we employ the recently developed threading assembly refinement (TASSER) method to generate structure predictions for all 907 putative GPCRs in the human genome. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. These features are essential for the comprehensive modeling of all human GPCRs when close homologous templates are absent. Based on a benchmarked confidence score, approximately 820 predicted models should have the correct folds. The majority of GPCR models share the characteristic seven-transmembrane helix topology, but 45 ORFs are predicted to have different structures. This is due to GPCR fragments that are predominantly from extracellular or intracellular domains as well as database annotation errors. Our preliminary validation includes the automated modeling of bovine rhodopsin, the only solved GPCR in the Protein Data Bank. With homologous templates excluded, the final model built by TASSER has a global C(alpha) root-mean-squared deviation from native of 4.6 angstroms, with a root-mean-squared deviation in the transmembrane helix region of 2.1 angstroms. Models of several representative GPCRs are compared with mutagenesis and affinity labeling data, and consistent agreement is demonstrated. Structure clustering of the predicted models shows that GPCRs with similar structures tend to belong to a similar functional class even when their sequences are diverse. These results demonstrate the usefulness and robustness of the in silico models for GPCR functional analysis. All predicted GPCR models are freely available for noncommercial users on our Web site (http://www.bioinformatics.buffalo.edu/GPCR).

Dataset Information

Modeling G Protein-Coupled Receptors: a Concrete Possibility.

Publications

Modeling G Protein-Coupled Receptors: a Concrete Possibility.

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