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.

Details

Title
Artificial intelligence-enabled discovery of a RIPK3 inhibitor with neuroprotective effects in an acute glaucoma mouse model
Author
Tu Xing 1 ; Zou Zixing 2 ; Li, Jiahui 3 ; Zeng Simiao 3 ; Luo Zhengchao 4 ; Li, Gen 5 ; Gao Yuanxu 6 ; Zhang, Kang 7 

 Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, Guangdong 510530, China; Guangzhou National Laboratory, Guangzhou International Bio Island, Guangzhou, Guangdong 510530, China; State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, Guangdong 510623, China; University of Chinese Academy of Sciences, Beijing 100049, China 
 Guangzhou National Laboratory, Guangzhou International Bio Island, Guangzhou, Guangdong 510530, China 
 Guangzhou National Laboratory, Guangzhou International Bio Island, Guangzhou, Guangdong 510530, China; State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, Guangdong 510623, China; Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, Guangdong 510623, China 
 Department of Big Data and Biomedical AI, College of Future Technology, Peking University, Beijing 100871, China 
 Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, Guangdong 510623, China 
 Guangzhou National Laboratory, Guangzhou International Bio Island, Guangzhou, Guangdong 510530, China; Institute for Artificial Intelligence in Medicine and Faculty of Medicine, Macau University of Science and Technology, Macao Special Administrative Region 999078, China 
 Guangzhou National Laboratory, Guangzhou International Bio Island, Guangzhou, Guangdong 510530, China; State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, Guangdong 510623, China; Institute for Artificial Intelligence in Medicine and Faculty of Medicine, Macau University of Science and Technology, Macao Special Administrative Region 999078, China 
Pages
172-184
Section
Original Article
Publication year
2025
Publication date
Jan 2025
Publisher
Lippincott Williams & Wilkins Ovid Technologies
ISSN
03666999
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3157050235
Copyright
Copyright © 2024 The Chinese Medical Association, produced by Wolters Kluwer, Inc. under the CC-BY-NC-ND license. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.