Computational models of structure, dynamics and evolution of class A GPCRs

Method

MD simulations are a powerful tool to investigate conformational dynamics with atomic-level detail, simulating molecular behavior at conditions and timescales not accessible to most experiments. While highly CPU and GPU intensive, these the simulations are physically straightforward: the atoms of the molecules are modelled as charged spheres connected to each other with strings, and an equation of motion (Newton’s second, in most cases) is integrated discretely -with other physics-enforcing refinements- by so-called simulation engines, like GROMACS [4], which we used for this project. This produces a trajectory of the system, that represents a plausible way in which a protein would react from a given starting condition, representing different experimental setups. What is more, most of these simulation engines are specifically designed to exploit massively parallel architectures, so that trajectories can be computed much efficiently and robustly at NHR-FAU.

Results

The MD work carried out NHR-FAU was crucial in several aspects. In publication [2], the MD data guided how the experimental validation of our main finding was designed. Based on our MD trajectories, we suggested that a so-far undescribed intermediate conformation (Fig. 1a), characterized by a novel receptor—G-protein interface (Fig. 1b), played a role in the activation cycle of the GPCR—G-protein complex. We could observe, with unprecedented detail, exactly which residues intervened in the formation of the interface, and probed their function with mutagenesis experiments. We could also identify the signal-transmitting mechanism across the above-mentioned interface. This implies a network of residues and known GPCR and G protein structural elements spanning over 50 Angstrom (Å), propagating from the extracellular ligand binding pocket of the receptor to the intracellular nucleotide-binding pocket of the Gα subunit of the G protein (Fig. 1c). You can interactively see an a representative 3D trajectory in your browser here.

In publication [3], the MD work expanded a set of newly determined experimental structures for the same GPCR—G-protein system. In this case, the experimental setup re-started a halted system. Employing an innovative structure-determination technique, termed time-resolved Cryo Electron Microscopy, it was possible to track the time-dependent behaviour of a nucleotide-depleted conformation after re-activating conditions were imposed upon it. This produced a rich ensemble of intermediate structures which we, in turn, used to run a set of extensive MD simulations characterizing the overall behaviour, both of the individual states as well as the trends observed at different CryoEM time-points. By combining structural determinations with global trends (Fig. 1d) observed in our MD data, a cohesive behaviour could be detected, aligning the observations of [3] with those in [2] as two directions in which the receptor—G-protein system can function: One where the signal is transmitted from the receptor ligand to the nucleotide [2] and one where the signal is transmitted from the nucleotide back to the ligand [3] after the nucleotide exchange -which lies at the core of G protein signalling- has happened.

Outlook

This work combines powerful computational resources like the NHR-FAU infrastructure with state-of-the-art methods like CryoEM -among others- to provide access to otherwise inaccessible information about how a fundamental physiological process like GPCR—G-protein signaling works. We have exploited insights from MD simulations to design conclusive experiments and, conversely, MD simulations have been used to complement, validate and expand newly generated experimental information. 

[1] Conflitti, P., Lyman, E., Sansom, M. S. P., Hildebrand, P. W., Gutiérrez-de-Terán, H., Carloni, P., Ansell, T. B., Yuan, S., Barth, P., Robinson, A. S., Tate, C. G., Gloriam, D., Grzesiek, S., Eddy, M. T., Prosser, S., & Limongelli, V. Functional dynamics of G protein-coupled receptors reveal new routes for drug discovery. Nature reviews. Drug discovery (2025). [DOI; PubMed] 

[2] Batebi, H., Pérez-Hernández, G., Rahman, S.N. et al. Mechanistic insights into G-protein coupling with an agonist-bound G-protein-coupled receptor. Nat Struct Mol Biol 31, 1692–1701 (2024). https://doi.org/10.1038/s41594-024-01334-2

[3] Papasergi-Scott, M.M., Pérez-Hernández, G., Batebi, H. et al. Time-resolved cryo-EM of G-protein activation by a GPCR. Nature 629, 1182–1191 (2024). https://doi.org/10.1038/s41586-024-07153-1

[4] Abraham, M. J. et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1–2, 19–25 (2015).