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GPCR 3D homology models for ligand screening: lessons learned from blind predictions of adenosine A2a receptor complex.

ABSTRACT: Proteins of the G-protein coupled receptor (GPCR) family present numerous attractive targets for rational drug design, but also a formidable challenge for identification and conformational modeling of their 3D structure. A recently performed assessment of blind predictions of adenosine A2a receptor (AA2AR) structure in complex with ZM241385 (ZMA) antagonist provided a first example of unbiased evaluation of the current modeling algorithms on a GPCR target with approximately 30% sequence identity to the closest structural template. Several of the 29 groups participating in this assessment exercise (Michino et al., doi: 10.1038/nrd2877) successfully predicted the overall position of the ligand ZMA in the AA2AR ligand binding pocket, however models from only three groups captured more than 40% the ligand-receptor contacts. Here we describe two of these top performing approaches, in which all-atom models of the AA2AR were generated by homology modeling followed by ligand guided backbone ensemble receptor optimization (LiBERO). The resulting AA2AR-ZMA models, along with the best models from other groups are assessed here for their vitual ligand screening (VLS) performance on a large set of GPCR ligands. We show that ligand guided optimization was critical for improvement of both ligand-receptor contacts and VLS performance as compared to the initial raw homology models. The best blindly predicted models performed on par with the crystal structure of AA2AR in selecting known antagonists from decoys, as well as from antagonists for other adenosine subtypes and AA2AR agonists. These results suggest that despite certain inaccuracies, the optimized homology models can be useful in the drug discovery process.

SUBMITTER: Katritch V

PROVIDER: S-EPMC2805832 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature

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GPCR 3D homology models for ligand screening: lessons learned from blind predictions of adenosine A2a receptor complex.

Katritch Vsevolod V Rueda Manuel M Lam Polo Chun-Hung PC Yeager Mark M Abagyan Ruben R

Proteins 20100101 1

Proteins of the G-protein coupled receptor (GPCR) family present numerous attractive targets for rational drug design, but also a formidable challenge for identification and conformational modeling of their 3D structure. A recently performed assessment of blind predictions of adenosine A2a receptor (AA2AR) structure in complex with ZM241385 (ZMA) antagonist provided a first example of unbiased evaluation of the current modeling algorithms on a GPCR target with approximately 30% sequence identity ...[more]

PMID: 20063437

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Project description:Adenosine receptors and ?-adrenoceptors are G-protein-coupled receptors (GPCRs) that activate intracellular G proteins on binding the agonists adenosine or noradrenaline, respectively. GPCRs have similar structures consisting of seven transmembrane helices that contain well-conserved sequence motifs, indicating that they are probably activated by a common mechanism. Recent structures of ?-adrenoceptors highlight residues in transmembrane region 5 that initially bind specifically to agonists rather than to antagonists, indicating that these residues have an important role in agonist-induced activation of receptors. Here we present two crystal structures of the thermostabilized human adenosine A(2A) receptor (A(2A)R-GL31) bound to its endogenous agonist adenosine and the synthetic agonist NECA. The structures represent an intermediate conformation between the inactive and active states, because they share all the features of GPCRs that are thought to be in a fully activated state, except that the cytoplasmic end of transmembrane helix 6 partially occludes the G-protein-binding site. The adenine substituent of the agonists binds in a similar fashion to the chemically related region of the inverse agonist ZM241385 (ref. 8). Both agonists contain a ribose group, not found in ZM241385, which extends deep into the ligand-binding pocket where it makes polar interactions with conserved residues in H7 (Ser?277(7.42) and His?278(7.43); superscripts refer to Ballesteros-Weinstein numbering) and non-polar interactions with residues in H3. In contrast, the inverse agonist ZM241385 does not interact with any of these residues and comparison with the agonist-bound structures indicates that ZM241385 sterically prevents the conformational change in H5 and therefore it acts as an inverse agonist. Comparison of the agonist-bound structures of A(2A)R with the agonist-bound structures of ?-adrenoceptors indicates that the contraction of the ligand-binding pocket caused by the inward motion of helices 3, 5 and 7 may be a common feature in the activation of all GPCRs.

Project description:Conventional methods to measure ligand-receptor binding parameters typically require radiolabeled ligands as probes. Despite the robustness of radioligand binding assays, they carry inherent disadvantages in terms of safety precautions, expensive synthesis, special lab requirements, and waste disposal. Mass spectrometry (MS) is a method that can selectively detect ligands without the need of a label. The sensitivity of MS equipment increases progressively, and currently, it is possible to detect low ligand quantities that are usually found in ligand binding assays. We developed a label-free MS ligand binding (MS binding) assay on the adenosine A(1) and A(2A) receptors (A(1)AR and A(2A)AR), which are well-characterized members of the class A G protein-coupled receptor (GPCR) family. Radioligand binding assays for both receptors are well established, and ample data is available to compare and evaluate the performance of an MS binding assay. 1,3-Dipropyl-8-cyclopentyl-xanthine (DPCPX) and 4-(2-((7-amino-2-(furan-2-yl)-[1,2,4]triazolo[1,5-a]-[1,3,5]triazin-5-yl)amino)ethyl)phenol (ZM-241,385) are high-affinity ligands selective for the A(1)AR and A(2A)AR, respectively. To proof the feasibility of MS binding on the A(1)AR and A(2A)AR, we first developed an MS detection method for unlabeled DPCPX and ZM-241,385. To serve as internal standards, both compounds were also deuterium-labeled. Subsequently, we investigated whether the two unlabeled compounds could substitute for their radiolabeled counterparts as marker ligands in binding experiments, including saturation, displacement, dissociation, and competition association assays. Furthermore, we investigated the accuracy of these assays if the use of internal standards was excluded. The results demonstrate the feasibility of the MS binding assay, even in the absence of a deuterium-labeled internal standard, and provide great promise for the further development of label-free assays based on MS for other GPCRs.

Project description:BACKGROUND: G protein-coupled receptors (GPCRs) transduce a wide variety of extracellular signals to within the cell and therefore have a key role in regulating cell activity and physiological function. GPCR malfunction is responsible for a wide range of diseases including cancer, diabetes and hyperthyroidism and a large proportion of drugs on the market target these receptors. The three dimensional structure of GPCRs is important for elucidating the molecular mechanisms underlying these diseases and for performing structure-based drug design. Although structural data are restricted to only a handful of GPCRs, homology models can be used as a proxy for those receptors not having crystal structures. However, many researchers working on GPCRs are not experienced homology modellers and are therefore unable to benefit from the information that can be gleaned from such three-dimensional models. Here, we present a comprehensive database called the GPCR-SSFE, which provides initial homology models of the transmembrane helices for a large variety of family A GPCRs. DESCRIPTION: Extending on our previous theoretical work, we have developed an automated pipeline for GPCR homology modelling and applied it to a large set of family A GPCR sequences. Our pipeline is a fragment-based approach that exploits available family A crystal structures. The GPCR-SSFE database stores the template predictions, sequence alignments, identified sequence and structure motifs and homology models for 5025 family A GPCRs. Users are able to browse the GPCR dataset according to their pharmacological classification or search for results using a UniProt entry name. It is also possible for a user to submit a GPCR sequence that is not contained in the database for analysis and homology model building. The models can be viewed using a Jmol applet and are also available for download along with the alignments. CONCLUSIONS: The data provided by GPCR-SSFE are useful for investigating general and detailed sequence-structure-function relationships of GPCRs, performing structure-based drug design and for better understanding the molecular mechanisms underlying disease-associated mutations in GPCRs. The effectiveness of our multiple template and fragment approach is demonstrated by the accuracy of our predicted homology models compared to recently published crystal structures.

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GPCR 3D homology models for ligand screening: lessons learned from blind predictions of adenosine A2a receptor complex.

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GPCR 3D homology models for ligand screening: lessons learned from blind predictions of adenosine A2a receptor complex.

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