Learning the activation mechanism in G protein coupled receptors from free energy calculations

Background - G protein coupled receptors (GPCRs) are relevant drug targets, with approximately 26% of marketed drugs targeting this receptor family. These receptors exhibit intrinsic conformational dynamics that govern their activation, interaction with intracellular effector proteins, and subsequent signal transduction cascades. The activation mechanism of GPCRs unfolds over long timescales and involves intricate conformational changes, including the roto-translation motion of transmembrane helix 6 (TM6) and alterations in the contact maps of specific amino acids, referred to as microswitches. Obtaining a comprehensive understanding of GPCR activation mechanisms is highly sought after, as it would facilitate the design of biased signaling ligands. These ligands selectively activate specific microswitches and promote the coupling of the receptor with a particular effector protein, thereby preserving the desired pharmacological effect while minimizing adverse effects. While structural studies utilizing techniques like X-ray, Cryo-EM, and NMR have shed light on some aspects of GPCR dynamics, a comprehensive understanding of their activation mechanisms remains elusive. Atomistic simulations offer promise in elucidating GPCR conformational ensembles, although the large scale and extended timescales of GPCR conformational changes pose challenges for traditional simulation protocols like standard molecular dynamics.

The project - In the present project, we focus on adenosine receptors (ARs) and beta-adrenergic receptors (BARs), with the aim of developing a computational strategy to investigate receptor activation mechanisms at the atomic level. The study seeks to achieve three main objectives: 1) characterizing receptor functional states during activation, 2) understanding the effects of ligands on receptor states, and 3) examining receptor interactions with effector proteins.

Research strategy - The research is structured into six thematic Work Packages (WPs), each dedicated to a specific receptor subtype. Each WP encompasses tasks such as data collection, generation of conformational states, simulation of activation pathways, and binding simulations with effector proteins. The research approach entails studying receptors in both the apo and holo forms complexed with ligands exhibiting various activity profiles ranging from agonist to partial agonist and inverse agonist. Advanced free-energy calculations based on path collective variables metadynamics, along with machine learning algorithms like AlphaFold 2, are employed to enhance the sampling and prediction capabilities of receptors' conformational changes, leveraging existing structural data while overcoming dimensionality issues and limiting timescale.

Impact - The research outcomes will significantly advance our understanding of receptor functionality. Firstly, we will reveal whether the investigated receptors assume key functional states, including intermediate and pre-active states, during their transition from the inactive to the active state. Secondly, our inquiry will elucidate the influence of the diverse ligands on the receptor's conformational equilibrium and subsequent interaction with effector proteins. By comparing structures obtained for diverse receptors within the same receptor subgroup (i.e., ARs or BARs), and when bound to different ligands, we could provide a structural foundation for understanding selective receptor activation and ligand-biased signaling pathways. This information is essential for designing ligands with tailored pharmacological activity and has the potential to revolutionize drug design for neurological, cardiovascular, and inflammatory disorders in the case of ARs and BARs, with significant societal and economic impact.