Novak Richard, Lin Tiffany, Kaushal Shruti, Sperry Megan, Vigneault Frederic, Gardner Erica, Loomba Sahil, Shcherbina Kostyantyn, Keshari Vishal, Dinis Alexandre, Vasan Anish, Chandrasekhar Vasanth, Takeda Takako, Nihalani Rahul, Umur Sevgi, Turner Jerrold R, Levin Michael, Ingber Donald E
Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
Unravel Biosciences, Inc., Boston, MA, USA.
Commun Med (Lond). 2025 Jul 1;5(1):249. doi: 10.1038/s43856-025-00975-8.
Many neurodevelopmental genetic disorders, such as Rett syndrome, are caused by a single gene mutation but trigger changes in expression of numerous genes. This impairs functions of multiple organs beyond the central nervous system (CNS), making it difficult to develop broadly effective treatments based on a single drug target. This is further complicated by the lack of sufficiently broad and biologically relevant drug screens, and the inherent complexity in identifying clinically relevant targets responsible for diverse phenotypes that involve multiple organs.
Here, we use computational drug prediction that combines artificial intelligence, human gene regulatory network analysis, and in vivo screening in a CRISPR-edited, Xenopus laevis tadpole model of Rett syndrome to carry out target-agnostic drug discovery. Four-week-old MeCP2-null male mice expressing the Rett phenotype are used to validate the therapeutic efficacy.
This approach identifies the FDA-approved drug, vorinostat, which broadly improves both CNS and non-CNS (e.g., gastrointestinal, respiratory, inflammatory) abnormalities in X. laevis and MeCP2-null mice. To our knowledge, this is the first Rett syndrome treatment to demonstrate pre-clinical efficacy across multiple organ systems when dosed after the onset of symptoms. Gene network analysis also reveals a putative therapeutic mechanism for the cross-organ normalizing effects of vorinostat based on its impact on acetylation metabolism and post-translational modifications of microtubules.
Although vorinostat is an inhibitor of histone deacetylases (HDAC), it unexpectedly reverses the Rett phenotype by restoring protein acetylation across hypo- and hyperacetylated tissues, suggesting its activity is based on a previously unknown therapeutic mechanism.
许多神经发育性遗传疾病，如雷特综合征，是由单个基因突变引起的，但会引发众多基因表达的变化。这会损害中枢神经系统（CNS）以外的多个器官的功能，使得基于单一药物靶点开发广泛有效的治疗方法变得困难。由于缺乏足够广泛且具有生物学相关性的药物筛选，以及在识别导致涉及多个器官的不同表型的临床相关靶点方面存在内在复杂性，情况进一步复杂化。
在这里，我们使用结合人工智能、人类基因调控网络分析和在雷特综合征的CRISPR编辑非洲爪蟾蝌蚪模型中进行体内筛选的计算药物预测，来进行无靶点药物发现。使用表达雷特表型的四周龄MeCP2基因敲除雄性小鼠来验证治疗效果。
这种方法鉴定出了美国食品药品监督管理局（FDA）批准的药物伏立诺他，它能广泛改善非洲爪蟾和MeCP2基因敲除小鼠的中枢神经系统和非中枢神经系统（如胃肠道、呼吸系统、炎症）异常。据我们所知，这是第一种在症状出现后给药时能在多个器官系统中显示临床前疗效的雷特综合征治疗方法。基因网络分析还揭示了伏立诺他基于其对乙酰化代谢和微管翻译后修饰的影响而产生的跨器官归一化作用的一种假定治疗机制。
尽管伏立诺他是组蛋白脱乙酰酶（HDAC）的抑制剂，但它通过恢复低乙酰化和高乙酰化组织中的蛋白质乙酰化，意外地逆转了雷特表型，这表明其活性基于一种先前未知的治疗机制。
