课题基金 / 基金详情

High Throughput Screening for Biased Agonists of the TSH Receptor that Activate the Beta-arrestin pathway

High Throughput Screening for Biased Agonists of the TSH Receptor that Activate the Beta-arrestin pathway
高通量筛选激活 β-抑制蛋白途径的 TSH 受体偏向激动剂
批准号：
10688945
负责人：
Juan Marugan
金额：
$42.54万
依托单位：
NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
--
资助国家：
美国
项目状态：
未结题
起止时间：
至
来源：
https://reporter.nih.gov/project-details/10688945
关键词：
AgonistArrestin Beta 1BiologyCell LineCollaborationsDiseaseEvaluationExtramural ActivitiesGoalsInformaticsMetabolicModelingOsteoporosisPathway interactionsPharmaceutical ChemistryPhenotypeProcessResearchResearch PersonnelSeriesSignal TransductionSynthesis ChemistryTestingThyrotropin ReceptorTranslationsUnited States National Institutes of HealthValidationWorkanalogassay developmentbasebeta-arrestindrug developmentdrug discoveryfollow-uphigh throughput screeninglead optimizationmouse modelnew technologynoveloverexpressionscreeningsmall moleculesmall molecule therapeuticstherapeutic developmenttool

项目摘要

项目成果

Juan Marugan的其他基金

相关文献

中文摘要
翻译
本项目的主要目标是开发一种有效的和选择性的小分子TSHR激动剂，具有偏性信号特征。 在此期间，从高通量筛选中鉴定出最有希望的命中物，并随后进行药物化学，合成了几个系列的类似物。用药物化学研究具有吸引人的活性特征的候选物，以合成一系列新的类似物，这些类似物被用于在TSHR过表达细胞系中进行测试，以确定β-Arrestin 1信号传导。对最有效、选择性和代谢稳定的分子进行了药代动力学研究。优化的先导分子正在骨质疏松症小鼠模型的有效性中进行评估。
英文摘要
The main goal of this project is to develop a potent and selective small molecule TSHR agonist, with biased signaling profile. During this period, the most promising hits from high-throughput screening were identified and followed up with medicinal chemistry and several series of analogs were synthesized. Candidates with attractive activity profiles were pursued with medicinal chemistry to synthesize a series of new analogs, which were advanced for testing in a TSHR overexpressing cell line to determine beta-Arrestin 1 signaling. Pharamcokinetics of the most potent, selective and metabolically stable molecules were carried out. The optimized lead molecule is under evaluation in efficacy mouse models of osteoporosis.
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