Simulação computacional das interações moleculares entre GPR3 e agonistas inversos

• Autor(a) principal: Russo, Silvana da Cunha
• Data de Publicação: 2019
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da PUC_RS
• Texto Completo: http://tede2.pucrs.br/tede2/handle/tede/8911
• topic: GPR3; Receptores Ligados a Proteína G; Doença de Alzheimer; Neurodegeneração; Neuroinflamação; Canabidiol; GPR3; G Protein Coupled Receptors; Alzheimer´s Disease; Neurodegeneration; Neuroinflammation; Cannabidiol; CIENCIAS DA SAUDE::MEDICINA

Neurodegenerative diseases are considered a burden to the ageing population. They represent a number of different pathologies which have different symptoms. (ZUCCHELLA et al., 2018). Until now, there was no viable treatment, just ways to alleviate the symptoms. (GAUTHIER et al., 2018). In the research of neurodegenerative diseases, several molecular targets are proposed. Among them, the G Protein Coupled Receptors (GPCR) group has been widely studied by the pharmaceutical industry, with a significant number of drugs approved to treat human diseases (HUANG et al., 2017). Recently, the orphan receptor GPR3, from the GPCR family, for which no endogenous ligand has yet been found, has been researched in Alzheimer´s Disease (LAUN et al., 2018). It is expressed broadly in the Central Nervous System, and its relation to neurodegenerative disease has been brought to light in Alzheimer´s Disease model research (THATHIAH et al., 2009). Some studies had now discovered a few ligands to GPR3 (JENSEN et al., 2014, LAUN; SONG, 2017). The investigation of GPR3 molecular interactions with its newly found ligands could help in the development of new drugs to treat neurodegenerative diseases. The main challenge in this investigation is the lack of available 3D structure for GPR3, which we intend to address using computational simulations. Computational methods bring agility and affordability to drug development.