How G protein-coupled receptor conformational dynamics control G protein coupling to trigger signaling is a key but still open question. We addressed this question with a model system composed of the purified ghrelin receptor assembled into lipid discs. Combining receptor labeling through genetic incorporation of unnatural amino acids, lanthanide resonance energy transfer, and normal mode analyses, we directly demonstrate the occurrence of two distinct receptor:Gq assemblies with different geometries whose relative populations parallel the activation state of the receptor. The first of these assemblies is a preassembled complex with the receptor in its basal conformation. This complex is specific of Gq and is not observed with Gi. The second one is an active assembly in which the receptor in its active conformation triggers G protein activation. The active complex is present even in the absence of agonist, in a direct relationship with the high constitutive activity of the ghrelin receptor. These data provide direct evidence of a mechanism for ghrelin receptor-mediated Gq signaling in which transition of the receptor from an inactive to an active conformation is accompanied by a rearrangement of a preassembled receptor:G protein complex, ultimately leading to G protein activation and signaling.GPCR | G protein | preassembly | conformation dynamics | signaling G protein-coupled receptors (GPCRs), one of the largest cell surface receptor families, are involved in many cellular signaling processes (1). Based on this property, as well as their importance as drug targets, the molecular aspects of GPCR functioning have been extensively investigated. In particular, coupling to heterotrimeric G proteins has been the focus of numerous studies. Indeed, delineating the molecular mechanisms responsible for receptor:G protein interaction is absolutely required to better understand how signaling is controlled. Recent years have seen spectacular advances that have culminated in elucidation of the 3D structure of the β 2 -adrenergic receptor:Gs complex (2). Nevertheless, the need for further progress remains, in particular to fully understand the dynamics of this interaction. This is a crucial question, given that how the receptor interacts with its G protein partner governs signaling, and thus biological and pathophysiological responses.To date, two different models for GPCR:G protein interaction have been proposed: collision coupling and preassembly. Originally, it was proposed that receptors and G proteins couple by collision (3, 4). One of the main features of this model is that only activated receptors interact with G proteins. Since then, alternative models of signaling have been developed. One of these, the preassembly model, proposes that the receptor and the G protein make a complex even in the absence of agonist (5-8).

Adaptive metabolic reprogramming gives cancer cells a proliferative advantage. Tumour cells extensively use glycolysis to sustain anabolism and produce serine, which not only refuels the one-carbon units necessary for the synthesis of nucleotide precursors and for DNA methylation, but also affects the cellular redox homeostasis. Given its central role in serine metabolism, serine hydroxymethyltransferase (SHMT), a pyridoxal 5 0 -phosphate (PLP)-dependent enzyme, is an attractive target for tumour chemotherapy. In humans, the cytosolic isoform (SHMT1) and the mitochondrial isoform (SHMT2) have distinct cellular roles, but high sequence identity and comparable catalytic properties, which may complicate development of successful therapeutic strategies. Here, we investigated how binding of the cofactor PLP controls the oligomeric state of the human isoforms. The fact that eukaryotic SHMTs are tetrameric proteins while bacterial SHMTs function as dimers may suggest that the quaternary assembly in eukaryotes provides an advantage to fine-tune SHMT function and differentially regulate intertwined metabolic fluxes, and may provide a tool to address the specificity problem. We determined the crystal structure of SHMT2, and compared it to the apo-enzyme structure, showing that PLP binding triggers a disorder-to-order transition accompanied by a large rigid-body movement of the two cofactor-binding domains. Moreover, we demonstrated that SHMT1 exists in solution as a tetramer, both in the absence and presence of PLP, while SHMT2 undergoes a dimer-to-tetramer transition upon PLP binding. These findings indicate an unexpected structural difference between the two human SHMT isoforms, which opens new perspectives for understanding their differing behaviours, roles or regulation mechanisms in response to PLP availability in vivo.

Proteins are found in solution as ensembles of conformations in dynamic equilibrium. Exploration of functional motions occurring on micro- to millisecond time scales by molecular dynamics (MD) simulations still remains computationally challenging. Alternatively, normal mode (NM) analysis is a well-suited method to characterize intrinsic slow collective motions, often associated with protein function, but the absence of anharmonic effects preclude a proper characterization of conformational distributions in a multidimensional NM space. Using both methods jointly appears to be an attractive approach that allows an extended sampling of the conformational space. In line with this view, the MDeNM (molecular dynamics with excited normal modes) method presented here consists of multiple-replica short MD simulations in which motions described by a given subset of low-frequency NMs are kinetically excited. This is achieved by adding additional atomic velocities along several randomly determined linear combinations of NM vectors, thus allowing an efficient coupling between slow and fast motions. The relatively high-energy conformations generated with MDeNM are further relaxed with standard MD simulations, enabling free energy landscapes to be determined. Two widely studied proteins were selected as examples: hen egg lysozyme and HIV-1 protease. In both cases, MDeNM provides a larger extent of sampling in a few nanoseconds, outperforming long standard MD simulations. A high degree of correlation with motions inferred from experimental sources (X-ray, EPR, and NMR) and with free energy estimations obtained by metadynamics was observed. Finally, the large sets of conformations obtained with MDeNM can be used to better characterize relevant dynamical populations, allowing for a better interpretation of experimental data such as SAXS curves and NMR spectra.