Advances in Structure Determination of G Protein-Coupled Receptors by SFX

AbstractCryo-electron microscopy (cryo-EM) experienced game-changing hardware and software advances about a decade ago. Since then, there have been gradual and steady improvements in experimental and data analysis methods. Nonetheless, structural analysis of nonsymmetric membrane proteins, such as G protein-coupled receptors (GPCRs), remains challenging. Their relatively low molecular weight and obstruction by the micelle/nanodisc result in marginal signal levels, which combined with the intrinsic flexibility of such complexes creates difficult structural study scenarios. Pushing the performance limits of cryo-EM requires careful optimization of all experimental aspects. To this end, it is necessary to build quantitative knowledge of the effect each parameter has on the outcome. Here, we present in-depth analysis of the influence of the main cryo-EM experimental factors on the performance for GPCR structure determination. We used a tandem experiment approach that combined real-world structural studies with parameter testing. We quantified the effects of using a Volta phase plate, zero-loss energy filtering, objective lens aperture, defocus magnitude, total exposure, and grid type. Through such systematic optimization of the experimental conditions, it has been possible to routinely determine class B1 GPCR structures at resolutions better than 2.5 Å. The improved fidelity of such maps helps to build higher confidence atomic models and will be crucial for the future expansion of cryo-EM into the structure-based drug design domain. The optimization guidelines drafted here are not limited to GPCRs and can be applied directly for the study of other challenging membrane protein targets.

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A synthetic method to assay adhesion-family G-protein coupled receptors. Determination of the G-protein coupling profile of ADGRG6(GPR126)

Biochemical and Biophysical Research Communications ◽

10.1016/j.bbrc.2020.11.086 ◽

2021 ◽

Vol 534 ◽

pp. 317-322

Author(s):

Enric Lizano ◽

Jozie L. Hayes ◽

Francis S. Willard

Keyword(s):

G Protein ◽

G Protein Coupled Receptors ◽

Synthetic Method ◽

G Protein Coupling ◽

Protein Coupling ◽

G Protein Coupled

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Signal transmission via G protein-coupled receptors in the light of rhodopsin structure determination.

Acta Biochimica Polonica ◽

10.18388/abp.2001_3892 ◽

2001 ◽

Vol 48 (4) ◽

pp. 1203-1207 ◽

Cited By ~ 3

Author(s):

J Ciarkowski ◽

P Drabik ◽

A Giełdoń ◽

R Kaźmierkiewicz ◽

R Slusarz

Keyword(s):

G Protein ◽

G Proteins ◽

Structure Determination ◽

Signal Transmission ◽

G Protein Coupled Receptors ◽

Atomic Resolution ◽

Gtp Binding ◽

External Signals ◽

G Protein Coupled ◽

Experimental Structure

G protein-coupled receptors (GPCRs) transducing diverse external signals to cells via activation of heterotrimeric GTP-binding (G) proteins, estimated to mediate actions of 60% of drugs, had been resistant to structure determination until summer 2000. The first atomic-resolution experimental structure of a GPCR, that of dark (inactive) rhodopsin, thus provides a trustworthy 3D prototype for antagonist-bound forms of this huge family of proteins. In this work, our former theoretical GPCR models are evaluated against the new experimental template. Subsequently, a working hypothesis regarding the signal transduction mechanism by GPCRs is presented.

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Precise modelling and interpretation of bioactivities of ligands targeting G protein-coupled receptors

Bioinformatics ◽

10.1093/bioinformatics/btz336 ◽

2019 ◽

Vol 35 (14) ◽

pp. i324-i332 ◽

Cited By ~ 1

Author(s):

Jiansheng Wu ◽

Ben Liu ◽

Wallace K B Chan ◽

Weijian Wu ◽

Tao Pang ◽

...

Keyword(s):

Neural Network ◽

G Protein ◽

Drug Targets ◽

Deep Neural Network ◽

Predictive Performance ◽

G Protein Coupled Receptors ◽

Supplementary Information ◽

Network Training ◽

G Protein Coupled

Abstract Motivation Accurate prediction and interpretation of ligand bioactivities are essential for virtual screening and drug discovery. Unfortunately, many important drug targets lack experimental data about the ligand bioactivities; this is particularly true for G protein-coupled receptors (GPCRs), which account for the targets of about a third of drugs currently on the market. Computational approaches with the potential of precise assessment of ligand bioactivities and determination of key substructural features which determine ligand bioactivities are needed to address this issue. Results A new method, SED, was proposed to predict ligand bioactivities and to recognize key substructures associated with GPCRs through the coupling of screening for Lasso of long extended-connectivity fingerprints (ECFPs) with deep neural network training. The SED pipeline contains three successive steps: (i) representation of long ECFPs for ligand molecules, (ii) feature selection by screening for Lasso of ECFPs and (iii) bioactivity prediction through a deep neural network regression model. The method was examined on a set of 16 representative GPCRs that cover most subfamilies of human GPCRs, where each has 300–5000 ligand associations. The results show that SED achieves excellent performance in modelling ligand bioactivities, especially for those in the GPCR datasets without sufficient ligand associations, where SED improved the baseline predictors by 12% in correlation coefficient (r2) and 19% in root mean square error. Detail data analyses suggest that the major advantage of SED lies on its ability to detect substructures from long ECFPs which significantly improves the predictive performance. Availability and implementation The source code and datasets of SED are freely available at https://zhanglab.ccmb.med.umich.edu/SED/. Supplementary information Supplementary data are available at Bioinformatics online.

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Toward G protein-coupled receptor structure-based drug design using X-ray lasers

IUCrJ ◽

10.1107/s2052252519013137 ◽

2019 ◽

Vol 6 (6) ◽

pp. 1106-1119 ◽

Cited By ~ 11

Author(s):

Andrii Ishchenko ◽

Benjamin Stauch ◽

Gye Won Han ◽

Alexander Batyuk ◽

Anna Shiriaeva ◽

...

Keyword(s):

Drug Design ◽

Crystal Structures ◽

G Protein ◽

Rapid Determination ◽

Binding Pocket ◽

G Protein Coupled Receptors ◽

Structure Based Drug Design ◽

G Protein Coupled ◽

Serial Femtosecond Crystallography

Rational structure-based drug design (SBDD) relies on the availability of a large number of co-crystal structures to map the ligand-binding pocket of the target protein and use this information for lead-compound optimization via an iterative process. While SBDD has proven successful for many drug-discovery projects, its application to G protein-coupled receptors (GPCRs) has been limited owing to extreme difficulties with their crystallization. Here, a method is presented for the rapid determination of multiple co-crystal structures for a target GPCR in complex with various ligands, taking advantage of the serial femtosecond crystallography approach, which obviates the need for large crystals and requires only submilligram quantities of purified protein. The method was applied to the human β2-adrenergic receptor, resulting in eight room-temperature co-crystal structures with six different ligands, including previously unreported structures with carvedilol and propranolol. The generality of the proposed method was tested with three other receptors. This approach has the potential to enable SBDD for GPCRs and other difficult-to-crystallize membrane proteins.

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