Combining pharmacology & AI to identify novel targets controlling proteostasis in neuronal cells

结合药理学

• 批准号: 2725951
• 金额: --
• 依托单位: Queen Mary University of London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2725951
• 关键词: Combining; pharmacology; AI; identify; novel

Neurodegenerative diseases (NDs) are debilitating conditions linked with aberrant health aging, akey BBSRC focus. Whilst the molecular origins for NDs are multiple, the dysregulation of proteinhomeostasis -or proteostasis- network, involving protein synthesis, folding & trafficking, is centralto the progression of NDs. This results in cellular stresses leading to cell death. At the molecularlevel, it is assumed that the accumulation of pathological aggregates result from non-physiologicalaggregation of proteins prone to misfolding, accumulating due to age-related deficits in proteostaticsystems, including the proteasome, mitochondrial dysfunction, stress & autophagic system.Our hypothesis is that although each ND involves distinct culprit proteins; commonregulatory nodes exist driving changes in protein homeostasis. Our aim is to use previouslydeveloped iPS cell models of NDs to identify targets for modulating proteostasis in neuronalcells. We will achieve this by harnessing Sosei-Heptares' in house AI & drug discoveryplatform coupled with well defined in house proprietary compounds.

神经退行性疾病（ND）是与异常健康衰老相关的衰弱性疾病，这是BBSRC的一个重点。虽然ND的分子起源是多方面的，但涉及蛋白质合成、折叠和运输的蛋白质稳态-或蛋白质稳态-网络的失调是ND进展的中心。这导致细胞应激，导致细胞死亡。在分子水平上，假设病理聚集体的积累是由于易于错误折叠的蛋白质的非生理性聚集，由于蛋白质稳态系统（包括蛋白酶体、线粒体功能障碍、应激和自噬系统）中与年龄相关的缺陷而积累。我们的假设是，尽管每个ND涉及不同的罪魁祸首蛋白质，但存在共同的调节节点来驱动蛋白质稳态的变化。我们的目的是利用以前开发的神经营养不良的iPS细胞模型来确定调节神经细胞蛋白质稳态的靶点。我们将通过利用Sosei-Heparin的内部AI和药物发现平台以及内部定义明确的专有化合物来实现这一目标。