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January 3, 2025 — A groundbreaking study has utilized artificial intelligence (AI) to uncover promising drug candidates for the treatment of glaucoma, a progressive eye disorder that affects millions of people worldwide. The research, led by Dr. Yuanxu Gao from Macau University of Science and Technology and Professor Zhang Kang from Guangzhou National Laboratory, marks a significant step toward the development of neuroprotective therapies for glaucoma, an eye condition that can lead to blindness if left untreated.
Glaucoma, characterized by elevated intraocular pressure and the gradual degeneration of retinal ganglion cells (RGCs), is responsible for optic nerve damage and vision loss. By 2040, it is estimated that over 111 million people worldwide will suffer from glaucoma, with no definitive cure currently available. While existing treatments manage ocular hypertension, they do not address the underlying damage to the optic nerve, making neuroprotection an essential focus of current research.
One of the key pathways implicated in the degeneration of RGCs is necroptosis, a programmed form of cell death that shares characteristics of both apoptosis (natural cell breakdown) and necrosis (injury-related cell damage). The receptor-interacting protein kinase 3 (RIPK3) molecule is known to play a crucial role in necroptosis, and its inhibition has emerged as a potential therapeutic target for preventing RGC loss and optic nerve damage.
In a bid to identify potential RIPK3 inhibitors, the research team leveraged AI-driven drug discovery techniques, such as virtual screening, quantitative structure-activity relationship modeling, and de novo drug design. These methods, powered by large language models and graph neural networks, enabled the researchers to generate a list of small-molecule compounds that could potentially target RIPK3. The AI models, including DynamicBind, predicted the affinity and interaction patterns of these compounds with RIPK3.
Through advanced molecular dynamics simulations and in silico analysis of absorption, distribution, metabolism, excretion, and toxicity (ADMET), the team narrowed down the list to five potent drug candidates: HG9-91-01, dabrafenib, AZD5423, GSK840, and HS-1371. Among these, HG9-91-01 emerged as the most promising candidate due to its strong binding affinity for RIPK3 and its favorable safety profile.
In laboratory experiments, HG9-91-01 demonstrated significant neuroprotective effects in an in vitro model of optic nerve damage. RGCs exposed to oxygen-glucose deprivation (OGD) showed improved survival rates when treated with HG9-91-01, with the compound reducing the presence of gasdermin D (GSDMD)-positive cells, a marker of pyroptosis, a form of inflammatory cell death. The compound also showed potential in preventing retinal thinning in mouse models, a common feature of glaucoma.
Professor Zhang Kang emphasized the novelty of the study, stating, “Although numerous studies have focused on anti-apoptotic, anti-necroptotic, and anti-pyroptotic drugs for treating acute ocular hypertension (AOH), strategies targeting PANoptosis, including cell-cell communication and cascade reactions of cell death, are rarely explored. Our study investigates RIPK3-targeting drugs to prevent RGC death and their role in preventing PANoptosis.”
The AI-driven approach to drug discovery not only accelerated the identification of promising candidates but also provided a logical, data-driven framework for future drug development. Dr. Gao noted, “AI technologies are invaluable for handling computationally intensive tasks, allowing us to make rational decisions based on complex, multimodal knowledge. However, potential concerns such as data privacy, transparency, and bias must be carefully addressed.”
While further confirmatory retinal assessments are needed to validate the efficacy of HG9-91-01 in protecting retinal structures in patients with AOH, the findings of this study represent an exciting step forward in the search for new treatments for glaucoma. With AI-powered innovations paving the way for faster and more accurate drug development, the future of glaucoma treatment is looking brighter.
For more information, refer to the study: Xing Tu et al., Artificial Intelligence-enabled Discovery of a RIPK3 Inhibitor with Neuroprotective Effects in an Acute Glaucoma Mouse Model, Chinese Medical Journal (2024). DOI: 10.1097/CM9.0000000000003387.
