RESUMO
Metabotropic glutamate receptors belong to a family of G protein-coupled receptors that are obligate dimers and possess a large extracellular ligand-binding domain that is linked via a cysteine-rich domain to their 7-transmembrane domain1. Upon activation, these receptors undergo a large conformational change to transmit the ligand binding signal from the extracellular ligand-binding domain to the G protein-coupling 7-transmembrane domain2. In this manuscript, we propose a model for a sequential, multistep activation mechanism of metabotropic glutamate receptor subtype 5. We present a series of structures in lipid nanodiscs, from inactive to fully active, including agonist-bound intermediate states. Further, using bulk and single-molecule fluorescence imaging, we reveal distinct receptor conformations upon allosteric modulator and G protein binding.
Assuntos
Ligantes , Domínios Proteicos , Receptor de Glutamato Metabotrópico 5 , Humanos , Regulação Alostérica/efeitos dos fármacos , Fluorescência , Modelos Moleculares , Ligação Proteica , Receptor de Glutamato Metabotrópico 5/agonistas , Receptor de Glutamato Metabotrópico 5/química , Receptor de Glutamato Metabotrópico 5/metabolismo , Imagem Individual de Molécula , Proteínas Heterotriméricas de Ligação ao GTP/metabolismoRESUMO
The world has witnessed a revolution in therapeutics with the development of biological medicines such as antibodies and antibody fragments, notably nanobodies. These nanobodies possess unique characteristics including high specificity and modulatory activity, making them promising candidates for therapeutic applications. Identifying their binding mode is essential for their development. Experimental structural techniques are effective to get such information, but they are expensive and time-consuming. Here, we propose a computational approach, aiming to identify the epitope of a nanobody that acts as an agonist and a positive allosteric modulator at the rat metabotropic glutamate receptor 5. We employed multiple structure modeling tools, including various artificial intelligence algorithms for epitope mapping. The computationally identified epitope was experimentally validated, confirming the success of our approach. Additional dynamics studies provided further insights on the modulatory activity of the nanobody. The employed methodologies and approaches initiate a discussion on the efficacy of diverse techniques for epitope mapping and later nanobody engineering.