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Doctoral thesis
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Personalized Drug Discoveries for Patients with GNAO1 Encephalopathies

Number of pages152
Imprimatur date2023
Defense date2023
Abstract

GNAO1 encephalopathy is a group of neurodevelopmental disorders caused by mutations in the GNAO1 gene encoding the major neuronal G protein, Gαo. Patients with this disease suffer from a broad range of symptoms, including epilepsy, movement disorders, hypotonia, and developmental delay. Unfortunately, a large subset of patients are refractory to available medications for epilepsy and movement disorders.

This thesis work is part of the basic and translational projects that aim to understand the molecular defects of pathogenic Gαo, followed by personalized drug discovery based on the specific biological properties of the variant. More than 80 pathogenic variants of Gαo have been identified, and in this study, we focus on four most recurrent variants: G203R, R209C, E246K, and T241_N242insPQ. Using in vitro biochemical assay, cellular assay, and molecular modeling, we unraveled the molecular defects of these pathogenic Gαo. These understanding then led us to develop a personalized drug discovery pipeline for different pathogenic Gαo. High-throughput screening (HTS) assays were performed to find small molecules that might, at least partially, correct the defect of the mutant Gαo. Hits validated in vitro and in cellular assays were then validated in vivo in the animal model of GNAO1 encephalopathy.

Overall, our works have pioneered a personalized drug discovery approach for GNAO1 encephalopathy.

eng
Keywords
  • GNAO1 encephalopathy
  • Rare disease
  • Neurodevelopmental disorder
  • G protein
  • Genetic disease
  • Drug discovery
  • Personalized medicine
  • High-throughput screening
  • Drug repurposing
Citation (ISO format)
LARASATI, Yonika Arum. Personalized Drug Discoveries for Patients with GNAO1 Encephalopathies. 2023. doi: 10.13097/archive-ouverte/unige:172632
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Technical informations

Creation10/25/2023 1:42:44 PM
First validation11/02/2023 10:59:56 AM
Update time11/02/2023 10:59:56 AM
Status update11/02/2023 10:59:56 AM
Last indexation05/06/2024 5:16:08 PM
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