Artificial intelligence-enabled discovery of a RIPK3 inhibitor with neuroprotective effects in an acute glaucoma mouse model.

IF 7.5 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Chinese Medical Journal Pub Date : 2025-01-20 Epub Date: 2024-12-23 DOI:10.1097/CM9.0000000000003387
Xing Tu, Zixing Zou, Jiahui Li, Simiao Zeng, Zhengchao Luo, Gen Li, Yuanxu Gao, Kang Zhang
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引用次数: 0

Abstract

Background: Retinal ganglion cell (RGC) death caused by acute ocular hypertension is an important characteristic of acute glaucoma. Receptor-interacting protein kinase 3 (RIPK3) that mediates necroptosis is a potential therapeutic target for RGC death. However, the current understanding of the targeting agents and mechanisms of RIPK3 in the treatment of glaucoma remains limited. Notably, artificial intelligence (AI) technologies have significantly advanced drug discovery. This study aimed to discover RIPK3 inhibitor with AI assistance.

Methods: An acute ocular hypertension model was used to simulate pathological ocular hypertension in vivo . We employed a series of AI methods, including large language and graph neural network models, to identify the target compounds of RIPK3. Subsequently, these target candidates were validated using molecular simulations (molecular docking, absorption, distribution, metabolism, excretion, and toxicity [ADMET] prediction, and molecular dynamics simulations) and biological experiments (Western blotting and fluorescence staining) in vitro and in vivo .

Results: AI-driven drug screening techniques have the potential to greatly accelerate drug development. A compound called HG9-91-01, identified using AI methods, exerted neuroprotective effects in acute glaucoma. Our research indicates that all five candidates recommended by AI were able to protect the morphological integrity of RGC cells when exposed to hypoxia and glucose deficiency, and HG9-91-01 showed a higher cell survival rate compared to the other candidates. Furthermore, HG9-91-01 was found to protect the retinal structure and reduce the loss of retinal layers in an acute glaucoma model. It was also observed that the neuroprotective effects of HG9-91-01 were highly correlated with the inhibition of PANoptosis (apoptosis, pyroptosis, and necroptosis). Finally, we found that HG9-91-01 can regulate key proteins related to PANoptosis, indicating that this compound exerts neuroprotective effects in the retina by inhibiting the expression of proteins related to apoptosis, pyroptosis, and necroptosis.

Conclusion: AI-enabled drug discovery revealed that HG9-91-01 could serve as a potential treatment for acute glaucoma.

人工智能在急性青光眼小鼠模型中发现具有神经保护作用的RIPK3抑制剂。
背景:急性高眼压引起的视网膜神经节细胞(RGC)死亡是急性青光眼的重要特征。介导坏死性坏死的受体相互作用蛋白激酶3 (RIPK3)是RGC死亡的潜在治疗靶点。然而,目前对RIPK3治疗青光眼的靶向药物和机制的了解仍然有限。值得注意的是,人工智能(AI)技术极大地推动了药物发现。本研究旨在人工智能辅助下发现RIPK3抑制剂。方法:采用急性高眼压模型,在体内模拟病理性高眼压模型。我们采用了一系列人工智能方法,包括大型语言和图神经网络模型,来识别RIPK3的目标化合物。随后,通过分子模拟(分子对接、吸收、分布、代谢、排泄和毒性(ADMET)预测和分子动力学模拟)和生物实验(Western blotting和荧光染色)对这些候选靶点进行体外和体内验证。结果:人工智能驱动的药物筛选技术具有极大加快药物开发的潜力。利用人工智能方法发现的一种名为HG9-91-01的化合物对急性青光眼具有神经保护作用。我们的研究表明,AI推荐的5种候选物在缺氧和葡萄糖缺乏时都能保护RGC细胞的形态完整性,并且HG9-91-01比其他候选物具有更高的细胞存活率。此外,在急性青光眼模型中发现HG9-91-01具有保护视网膜结构和减少视网膜层丢失的作用。我们还观察到HG9-91-01的神经保护作用与抑制PANoptosis(凋亡、焦亡、坏死)高度相关。最后,我们发现HG9-91-01可以调节PANoptosis相关的关键蛋白,表明该化合物通过抑制凋亡、焦亡、坏死相关蛋白的表达,在视网膜中发挥神经保护作用。结论:人工智能支持的药物发现表明,HG9-91-01可能是治疗急性青光眼的潜在药物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Chinese Medical Journal
Chinese Medical Journal 医学-医学:内科
CiteScore
9.80
自引率
4.90%
发文量
19245
审稿时长
6 months
期刊介绍: The Chinese Medical Journal (CMJ) is published semimonthly in English by the Chinese Medical Association, and is a peer reviewed general medical journal for all doctors, researchers, and health workers regardless of their medical specialty or type of employment. Established in 1887, it is the oldest medical periodical in China and is distributed worldwide. The journal functions as a window into China’s medical sciences and reflects the advances and progress in China’s medical sciences and technology. It serves the objective of international academic exchange. The journal includes Original Articles, Editorial, Review Articles, Medical Progress, Brief Reports, Case Reports, Viewpoint, Clinical Exchange, Letter,and News,etc. CMJ is abstracted or indexed in many databases including Biological Abstracts, Chemical Abstracts, Index Medicus/Medline, Science Citation Index (SCI), Current Contents, Cancerlit, Health Plan & Administration, Embase, Social Scisearch, Aidsline, Toxline, Biocommercial Abstracts, Arts and Humanities Search, Nuclear Science Abstracts, Water Resources Abstracts, Cab Abstracts, Occupation Safety & Health, etc. In 2007, the impact factor of the journal by SCI is 0.636, and the total citation is 2315.
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