Computational Receptor Biology – Gloriam Group

Biased Signalling

1. Most GPCR ligands activate multiple signalling pathways spanning four G protein classes: G_q/11, G_i/o, G_s and G_12/13 with 16 subtypes. Furthermore, arrestin proteins mediate GPCR signalling, desensitisation and internalisation.

2. A biased ligand preferentially actives only one singnalling pathway. A new candidate analgesic drug, oliceridine selectively stimulates the μ-opioid receptor G_i/o pathway, but lacks the ß-arrestin mediated constipation and respiratory depression.

Drug development has an 86% failure rate –mainly due to insufficient efficacy or to side effects. For GPCRs this could be solved by ‘biased ligands’ which re-route cellular pathways to therapeutic actions away from side effects. However, this huge potential is inaccessible because few GPCRs have biased ligands and we do not yet know the molecular mechanisms to rationally design them.

Biased ligands: We will create a database of known biased ligands and identify new such ligands through computational drug design. A PhD training network, SAFER has set out to identify biased ligands for the serotonin 2A receptor (5-HT2A), which mediates the effect of recreational drugs, e.g. LSD and agents in clinical trials for treatment-resistant depression and anxiety. A Novo Nordisk Foundation Ascending Investigator grant focuses on the free fatty acid receptor 4 – a target for diabetes and inflammation – will also pharmacologically profile the signalling of known reference ligands and drugs to identify signalling bias. Going forward, we would like to take on a wider challenge to build a virtual screening pipeline to identify novel ligands with signalling bias for many more GPCRs.

Pathway effects: We will make an online atlas of the physiological and therapeutic effects of individual GPCR signalling pathways, thereby providing the rationale for which pathways to target in drug discovery and receptor function studies. So far, few such effects are known. However, much more such data will soon become available, from e.g. the new European research network on signal transduction, ‘ERNEST’ and as more clinical trials evaluate biased candidate drugs. We are also exploring computational drug design to identify G protein/b-arrestin inhibitors that would constitute very valuable tools to map (patho)physiological pathways.

Structures and mechanisms: We plan to (application pending) to develop protein engineering and online tools to ease the generation of GPCR structures bound to G proteins and biased ligands, which could elucidate molecular mechanisms to design biased tool compounds and drugs.

Computational drug design

Left) Docking of a ligand into the binding site of a receptor target structure provides a model of the mode-of-action, guiding further medicinal chemistry optimisation and pharmacological validation by mutagenesis.

Right) Pharmacophore elements are placed based on known ligands to give a 3D representation of the features important for target interaction and activity, and are used to identified new ligands with other chemical structures.

"Today the computer is just as important a tool for chemists as the test tube. Simulations are so realistic that they predict the outcome of traditional experiments"

- Finale of the motivation for the
- 2013 Nobel Prize in Chemistry

"Today, computational models are integral for the rationalization of experimental data and generation of hypotheses for new studies. In the Gloriam group, we combine bioinformatics, chemoinformatics and computational chemistry in computational drug design at GPCRs. We also develop new methods for virtual screening, chemogenomics and design of target-directed focused screening libraries.

The work has led to the identification of novel ligands for the chemokine, glutamate, histamine and serotonin receptors. It is highly interdisciplinary, building on collaborations with Medicinal Chemistry and Molecular Pharmacology groups at the Department of Drug Design and Pharmacology, as well as several international labs.

The explosion of biomedical data in genomics, structural biology and pharmacology provides new opportunities to deepen our understanding of human physiology and disease. We integrate these data with innovative computational tools to gain novel insights into receptor biology. Our strength is the combined expertise in selected biological systems with the integration of diverse often unique datasets and hypotheses. The common objective of our projects is to tackle some of the currently most sought-after questions in the GPCR field.

More information
Visit GPCRdb
NC-IUPHAR newsletter (pages 3-4)
GPCRdb poster
Popular scientific article (in Danish)

Selected Publications
GPCRdb in 2018: Adding GPCR structure models and ligands
Pándy-Szekeres G, Munk C, Tsonkov T, Mordalski S, Harpsøe K, Hauser AS, Bojarski AJ and Gloriam DE
Nucleic Acids Research. 2017

Munk C, Harpsøe H, Hauser A, Isberg V, and Gloriam DE
Integrating structural and mutagenesis data to elucidate GPCR ligand binding.
Curr Opin Pharmacol, 2016 Jul 28;30:51-58

Munk C, Isberg V, Mordalski S, Harpsøe K, Rataj K, Hauser A, Kolb P, Bojarski AJ, Vriend G, and Gloriam DE
GPCRdb: The G protein-coupled receptor database - An introduction.
Br J Pharmacol, 2016 Jul;173(14):2195-207

Isberg V, Mordalski S, Munk C, Rataj K, Harpsøe K, Hauser AS, Vroling B, Bojarski AJ, Vriend G, and Gloriam DE
GPCRdb: an information system for G protein-coupled receptors
Nucleic Acids Res, 2016 Jan 4;44(D1):D356-64

Isberg V, de Graaf C, Bortolato A, Cherezov V, Katritch V, Marshall FH, Mordalski S, Pin JP, Stevens RC, Vriend G, Gloriam DE.
Generic GPCR residue numbers - aligning topology maps while minding the gaps.
Trends Pharmacol Sci.  2015 Jan;36(1):22-31.; PMID: 25541108

Isberg V, Vroling B, van der Kant R, Li K, Vriend G and Gloriam DE
GPCRDB: information system for G protein-coupled receptors
Nucleic Acids Res. 2014 Jan 1;42(1); PMID: 24304901

GPCR structures are invaluable for receptor function studies and for rational drug design. Technological advances in X-ray crystallography and cryogenic electron microscopy (cryo-EM) have led to an explosion of structures covering all major GPCR classes and diverse ligands (see latest statistics). However, there are still no structures for the vast majority of the 398 non-olfactory GPCRs and technological limitations remain that restrict which ligand complexes can be attained.

In the last years, the Gloriam group has set up GPCR crystallography and cryo-EM in collaboration with structural biology professors Jette S. Kastrup and Michael Gajhede. The projects aim to cover more receptors and ligands, including in-house medicinal chemistry targets and biased ligands. We are part of a structural biology network, ISBUC at the University of Copenhagen. We collect data at the new state-of-the-art synchrotron MAX IV in Lund (X-ray crystallography), two national cryo-EM core facilities and a number of international resources.

The Gloriam group also maintain an online resource for GPCR structure determination based on all published structures. The major features include design of new receptor constructs and browsing of experimental methods and reagents (Structure Constructs section in https://gpcrdb.org). The GPCRdb database also features a number of tools to analyse existing structures and, where lacking, structure models for nearly all GPCRs in the inactive, active and intermediate states.