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Community-wide assessment of GPCR structure modelling and ligand docking: GPCR Dock 2008

Key Points

  • To evaluate current progress in GPCR structure prediction and ligand docking, a community-wide prediction assessment — GPCR Dock 2008 — in coordination with the publication of the human adenosine A2A receptor structure in October 2008 and public release of the 3-dimensional coordinates.

  • Twenty-nine groups submitted 206 structural models before the release of the experimental structure. The structures were evaluated for the accuracy of the ligand binding mode and the overall receptor model compared with the crystal structure.

  • The majority of the submitted models predicted the overall topology, but did not predict the ligand position and the binding interactions very accurately.

  • The best model overall (submitted by S. Costanzi) has a ligand RMSD of 2.8 Å RMSD and 34 of 75 correct contacts.

  • Accurate modelling of the structurally divergent regions (such as the extracellular loops), of disulphide bond formation affecting helix residue registry and of the helical shifts in the TM region seem to be crucial for accurately predicting the key ligand interactions in GPCRs, and this area is perhaps the most in need of technological development.


Recent breakthroughs in the determination of the crystal structures of G protein-coupled receptors (GPCRs) have provided new opportunities for structure-based drug design strategies targeting this protein family. With the aim of evaluating the current status of GPCR structure prediction and ligand docking, a community-wide, blind prediction assessment — GPCR Dock 2008 — was conducted in coordination with the publication of the crystal structure of the human adenosine A2A receptor bound to the ligand ZM241385. Twenty-nine groups submitted 206 structural models before the release of the experimental structure, which were evaluated for the accuracy of the ligand binding mode and the overall receptor model compared with the crystal structure. This analysis highlights important aspects for success and future development, such as accurate modelling of structurally divergent regions and use of additional biochemical insight such as disulphide bridges in the extracellular loops.

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Figure 1: Root mean square deviation (RMSD) of submitted models.
Figure 2: Statistics of the two key receptor–ligand interactions in all models.
Figure 3: Superposition of all 206 submitted models to the crystal structure of the human adenosine A2A receptor.
Figure 4: Model analysis.
Figure 5: Comparison between the best models and the crystal structure around the ligand-binding site.


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We thank M. Hanson, V.-P. Jaakola, C. Roth and V. Cherezov for help with the analysis and comments on the manuscript, and K. Kadyshevskaya and V. Cherezov for figure preparation. We are grateful to the Goddard group for providing the script to calculate the binding site contact RMSD. We thank A. Walker for data tracking and assistance with the manuscript and J. Kunken for IT help during the assessment. This work was supported in part by the Protein Structure Initiative grant U54 GM074961 (ATCG3D), the NIH Roadmap grant P50 GM073197 (JCIMPT), and the Multiscale Modeling Tools for Structural Biology NCRR via grant P41 RR012255.

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Correspondence to Raymond C. Stevens.

Supplementary information

Supplementary information S1 (box)

Computational methods used by the GPCR Dock 2008 participants (PDF 3365 kb)


Rhodopsin and bacteriorhodopsin

These two light-activated membrane proteins have a seven transmembrane alpha-helical bundle architecture that is similar to the general structure of the larger GPCR family.

Molecular dynamics simulation

This molecular modelling approach uses numerical integration to solve the equations of motion based on the forces arising from interatomic interactions. The dynamic behaviour of atoms in a macromolecular system, such as that in a membrane protein, can be understood by running a molecular dynamics (MD) simulation. MD simulation can also be used to refine structural models of proteins and protein–ligand complexes.

Ligand docking

A molecular modelling approach that predicts the ligand binding mode within a targeted binding site. In this approach, the known or predicted three-dimensional structure of a protein is probed using computationally generated energy landscapes to identify the most favourable binding pose for the ligand.

RMSD (root mean square deviation)

RMSD is used as a quantitative measure of the similarity between two superimposed atomic coordinates. RMSD values (units of Å) can be calculated for any type and subset of atoms; for example, Cα atoms of proteins (Cα RMSD) for all residues, for residues in the transmembrane helices or the loops; heavy atoms of small-molecule ligands (ligand RMSD).


A standard dimensionless score that normalizes a value with respect to the sample mean and standard deviation.

Cα atoms

The chiral carbon atoms to which the primary amine, the carboxylic group and the side chain are attached to in an amino acid. Comparison of three-dimensional structures of proteins is sometimes carried out by superimposing the Cα atoms of proteins as this provides a simple estimate of the similarity of their skeleton or backbone structure.


A descriptor that reflects the fluctuation of atomic position from an atom's average position and provides important insight into a protein's potential dynamic behaviour.

Hydrogen bond

Attractive interaction between one electronegative atom and a hydrogen covalently bonded to another electronegative atom such as nitrogen or oxygen.

Aromatic stacking

Attractive interactions between the aromatic rings of amino acids. Overlapping of p-orbitals of π-conjugated systems result in the rings arranging themselves in preferred orientations.

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Michino, M., Abola, E., GPCR Dock 2008 participants. et al. Community-wide assessment of GPCR structure modelling and ligand docking: GPCR Dock 2008. Nat Rev Drug Discov 8, 455–463 (2009).

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