LIFE SCIENCES

Introduction

G-protein coupled receptors (GPCRs) are membrane proteins that transmit the effects of extracellular ligands to effect changes in the intracellular G-protein signaling system. Approximately 800 GPCRs are encoded in the human genome and approximately half of all marketed drugs target GPCRs. It is therefore not surprising that GPCR-research was recognized by the award of the 2012 Nobel Prize in Chemistry to Robert Lefkowitz and Brian Kobilka. Crystal structures of only 113 different GPCRs are currently available. Importantly, GPCRs can exist in active or inactive conformations and in binary complexes with ligands or intracellular binding partners (IBPs, G-proteins or β-arrestin) or in ternary complexes with both a ligand and an IBP. Crystal structures often deviate from the natural system: Proteins, especially membrane-bound ones, do not necessarily crystallize in their biologically active structures and the measures needed to obtain suitable GPCR crystals tend to increase the diversity between the natural environment and the crystal. It is within this context that molecular-dynamics simulations play a special role in GPCR research as a full-value complement to experimental studies.

Very long timescale MD simulations can be performed on specialized hardware but are less effective on more conventional massively parallel supercomputers because the simulations only scale up to a relatively limited number of CPUs or GPUs. Luckily, modern variations of metadynamics can make very effective use of massively parallel cpu-based hardware, as has been shown in this project.

Results and Methods

GPCRs were investigated using classical (force-field) molecular-dynamics (MD) simulations on receptors embedded in a model membrane to represent the cell wall. Targeted MD was performed using a metadynamics protocol developed within the project. Most simulations use Gromacs 2019.4 and Plumed 2.5.3. Unbiased MD simulations achieved on average 200ns/day using 16 nodes (48 cores each) corresponding to ≈ 100 cpuh/ns on SuperMUC-ng. Metadynamics simulations perform similarly and converge within 2 μs ≈ 200,000 cpuh/run. Performance was optimized via the compute protocol, rather than by modifying software.

Receptor activation

Most of our work has centered on Class A GPCRs but we were able to identify the activation mechanism of a Class B receptor, the glucagon receptor, in very extensive metadynamics simulations with two collective variables. [1] We have now developed a general protocol to simulate the activation/deactivation free-energy profiles of Class A receptors that has proven to be very successful in investigating the effects of different types of ligand on the receptor’s conformational equilibria. Protocols have also been established to interpret these results in terms of the specific inter-residue interactions (“microswitches”) usually discussed for GPCR-activation.

Receptor-ligand interactions

We have used molecular dynamics simulations to study the interaction between cyclic peptides and the neuropeptide Y Y₄ receptor (Y₄R), which belongs to the Class A GPCRs. [2] These peptides bind Y₄R with picomolar affinity (Figure 1) and exhibit a considerably more pronounced Y₄R selectivity compared to previous ligands. Therefore, they represent promising leads the development of drug-like Y₄R ligands.

Receptor-catalyzed G protein activation

Our work is focused on the analysis of the formation of a productive complex of active receptor and G protein. Productive means that the receptor is observed catalyzing the nucleotide exchange in the G protein. In our unbiased all-atom MD simulations, the uncoupled receptor and GDP-bound inactive G protein spontaneously form a complex. Long-range allosteric effects are observed from the active receptor to the nucleotide, opening the nucleotide-binding pocket and breaking half of the GDP contacts. In subsequent umbrella sampling MD simulations, we observed the release of GDP from its binding pocket without touching the GDP. Our simulations provide insights into the structural mechanism the universal process of receptor-catalyzed G protein activation (see Figure 2 below). 

Ongoing Research / Outlook

As in previous funding periods, project pr94su has made significant advances in the field of GPCR simulations, both in terms of developing computational protocols and in contributing to mechanistic and structural GPCR research in general.  In the latter respect, the project has once more underlined the unusual importance in this experimentally very challenging field.

Our studies of the activation of GPCRs have reached a stage at which we now have a powerful tool for studying the activation/deactivation process in atomistic detail and can proceed to production simulations designed to answer open mechanistic questions. Future work will concentrate on the role of the pre-active conformation first revealed in atomistic detail in reference [1] and now routinely identifiable for class A GPCRs, and on the roles and conformational effects of different kinds of ligands, with special emphasis on allosteric modulators.

Our close connection with Research Training Center 1910 Medicinal Chemistry of selective GPCR ligands provides us with unique opportunities to extend the scope and conclusions of experimental studies by considering new ligand/receptor combinations for which unpublished experimental data are available. In this respect, our studies on receptor-ligand interactions contribute new fundamental knowledge to enhance the ligand-design process. Protocols developed together with Prof. Francesco Gervasio (Geneva) allow us to translate the simulation results into analyses familiar to experimental GPCR researchers.

Finally, our studies go one step further than analyzing the differently active conformations of the receptor itself to investigate the process by which the active conformation(s) of the receptor actually lead to signaling via G-protein activation. These studies represent a significant advance in the scope and applicability of GPCR simulations

References

[1] G. Mattedi, S. Acosta-Gutiérrez, T. Clark and F. L. Gervasio, Proc. Nat. Acad. Sci. USA (2020) 117, 15414-15422.

[2] A. Konieczny, M. Conrad, F. J. Ertl, J. Gleixner, A. O. Gattor, L. Grätz, M. F. Schmidt, E. Neu, A. H. C. Horn, D. Wifling, P. Gmeiner, T. Clark, H. Sticht and M. Keller, J. Med. Chem. (2021) 64, 16746-16769

Scientific Contact: 

Prof. Dr. Tim Clark
CCC, Nägelsbachstraße 25
91052 Erlangen
+49 9131 85-22948
tim.clark@fau.de