Addressing GPCR conformational flexibility

Funder

Royal Society

Value

£179,266 

Team

Professor Christopher A Reynolds

Collaborators

Sosei Heptares

Dates

1 October 2016 to 31 August 2021

Project overview

The large G protein coupled receptor (GPCR) family is a highly interesting target for drug design because a large proportion of current drugs bind to its members, and because the family offers much potential to exploit new targets. Advances in our understanding of GPCRs have heightened interest in rational drug design methods. The most notable advance is the ability to generate structures, either through X-ray crystallography or cryo-electron microscopy. However, GPCRs are not static structures and their ability to adopt multiple conformations under the actions of agonists, partial agonists, and allosteric modulators can lead to multiple activation pathways. This is significant because activation of one pathway by a drug may lead to beneficial effects, whereas parallel activation of an alternative pathway may lead to detrimental side effects.

To understand how a drug may be biased to a beneficial pathway, we have sought to use molecular dynamics (MD) simulations to understand more fully the conformational landscape of GPCRs in the presence of agonist.

Limitations in computer time generally restrict these simulations to lengths of ~1-10 μs, which is not necessarily sufficient to study relevant conformational transitions. Our approach to these is to use adaptive sampling whereby structural knowledge accumulated on previous simulations automatically directs the next round of MD sampling.

The background to this work lies in the discovery that different regions of the extracellular surface of the GLP-1 receptor, a class B GPCR involved in diabetes, are involved in the initiation of alternative signalling pathways1. This initial collaborative work was essentially based on a homology model of the GLP-1 receptor, but more recent work has been based on cryo-EM structures (in collaboration with Monash) augmented through modelling ^2-6. These simulations present a considerable challenge as they involve up to 6 proteins in the complex, and simulations over a few μs limit the extent of the observable conformational changes. However, Giuseppe Deganutti’s introduction of an adaptive sampling method, namely path-supervised molecular dynamics, SuMD(path), facilitated the dynamic docking of the secretin peptide to its receptor. The additional sampling of the SuMD(path)-derived binding pathway helped to explain the photoaffinity data that implicated regions of the peptide to be in contact with the receptor despite there being no contact in the cryo-EM structure. Adaptive sampling has also been effective in studying cooperative effects in the ligand (un)binding pathways of the free fatty acid receptor⁷.

While X-ray and cryo-EM structures are generally static, analysis of the dynamic data within the cryo-EM micrographs has highlighted the relative domain movement within the adrenomedullin-RAMP-G protein complexes⁸, which is consistent with our molecular dynamics simulations.

Impact

An understanding of how the different regions of the extracellular surface of the calcitonin and amylin receptors are involved in alternative signalling pathways^{5, 6}.

A full structure of the active complex of the CGRP receptor that can be used in drug design (e.g. migraine and cardiovascular disease).²

An understanding of the dynamics of the CGRP receptor, and how this is modulated by the obligate receptor activity modulating protein (RAMP). ²

A full structure of the active complex of the GLP-1 receptor with a non-peptidic agonist that can be used in drug design (e.g. obesity, diabetes)³.

Simulations on the GLP-1 receptor that indicate how conformational changes on activation compare for peptidic and non-peptidic agonists³.

A full structure of the secretin receptor that can be used in drug design (e.g. diabetes, obesity, heart failure)⁴.

Development of the path-Supervised molecular dynamics method for studying peptide binding⁴.

Insight into ligand (un)binding in the free fatty acid receptor (a diabetes drug target)⁷.

Structures of the adrenomedullin receptors (AM1, AM2) that can be used in drug design (relevant to cardiovascular disease and cancer) and to understand how RAMPs allosterically control the receptor⁸.

Understanding of the dynamic inter-domain movement in the RAMP-GPCR-G protein adrenomedullin receptor complexes that may underlie the signalling response⁸.

Outputs and references

1. Wootten, D.; Reynolds, C. A.; Smith, K. J.; Mobarec, J. C.; Koole, C.; Savage, E. E.; Pabreja, K.; Simms, J.; Sridhar, R.; Furness, S. G. The extracellular surface of the GLP-1 receptor is a molecular trigger for biased agonism. Cell 2016, 165, 1632-1643.
2. Liang, Y. L.; Khoshouei, M.; Deganutti, G.; Glukhova, A.; Koole, C.; Peat, T. S.; Radjainia, M.; Plitzko, J. M.; Baumeister, W.; Miller, L. J.; Hay, D. L.; Christopoulos, A.; Reynolds, C. A.; Wootten, D.; Sexton, P. M. Cryo-EM structure of the active, Gs-protein complexed, human CGRP receptor. Nature 2018, 561, 492-497.
3. Zhao, P.; Liang, Y. L.; Belousoff, M. J.; Deganutti, G.; Fletcher, M. M.; Willard, F. S.; Bell, M. G.; Christie, M. E.; Sloop, K. W.; Inoue, A.; Truong, T. T.; Clydsdale, L.; Furness, S. G.; Christopoulos, A.; Wang, M. W.; Reynolds, C. A.; Danev, R.; Sexton, P. M.; Wootten, D. Activation of the GLP-1 receptor by a non-peptidic agonist. Nature 2020, 577, 432-436.
4. Dong, M.; Deganutti, G.; Piper, S. J.; Liang, Y. L.; Khoshouei, M.; Belousoff, M. J.; Harikumar, K. G.; Reynolds, C. A.; Glukhovia, A.; Furness, S. G. B.; Christopoulos, A.; Danev, R.; Wootten, D.; Sexton, P. M.; Miller, L. J. Structure and dynamics of the active, Gs-coupled, human secretin receptor Nature communications 2020, 11, 4137.
5. Dal Maso, E.; Glukhova, A.; Zhu, Y.; Garcia-Nafria, J.; Tate, C. G.; Atanasio, S.; Reynolds, C. A.; Ramirez_Apoteia, E.; Carazo, J. M.; Hick, C. A.; Furness, S. G.; Hay, D. L.; Liang, Y. L.; Miller, L. J.; Christopoulos, A.; Wang, M.; Wootten, D.; Sexton, P. M. The Molecular Control of Calcitonin Receptor Signaling. ACS Pharmacol. Transl. Sci. 2019, 2, 31-51.
6. Pham, V.; Dal Maso, E.; Reynolds, C. A.; Deganutti, G.; Atanasio, S.; Hick, C.; Yang, D.; Christopoulos, A.; Hay, D. L.; Furness, S. G.; Wang, M. W.; Wootten, D.; Sexton, P. M. Deconvoluting the Molecular Control of Binding and Signaling at the Amylin 3 (AMY3) Receptor: RAMP3 Alters Signal Propagation Through Extracellular Loops of the Calcitonin Receptor. ACS Pharmacol. Transl. Sci., 2019, 2 183-197.
7. Atanasio, S.; Deganutti, G.; Reynolds, C. A. Addressing free fatty acid receptor 1 (FFAR1) activation using supervised molecular dynamics. J. Comput. Aided Mol. Des. 2020, 34, 1181-1193.
8. Liang, Y. L.; Belousoff, M. J.; Fletcher, M. M.; Zhang, X.; Khoshouei, M.; Deganutti, G.; Koole, C.; Furness, S. G. B.; Miller, L. J.; Hay, D. L.; Christopoulos, A.; Reynolds, C. A.; Danev, R.; Wootten, D.; Sexton, P. M. Structure and Dynamics of Adrenomedullin Receptors AM1 and AM2 Reveal Key Mechanisms in the Control of Receptor Phenotype by Receptor Activity-Modifying Proteins. ACS Pharmacol Transl Sci 2020, 3, 263-284.
9. Relevant PDB files: 6NIY, 6E3Y, 6WZG, 6E3Y, 6WI9, 6ORV, 6UUN, 6UUS 6UVA