A new study harnessing the power of AI has identified a promising drug candidate for treating glaucoma, revealing significant potential for future therapeutic developments. Researchers utilized AI models to pinpoint HG9-91-01 as a key RIPK3 inhibitor with neuroprotective properties, offering hope for glaucoma patients worldwide.
In a new study published in the Chinese Medical Journal, a team of researchers has utilized artificial intelligence to discover a promising new drug candidate for glaucoma treatment. Led by Yuanxu Gao, a postdoctoral fellow at Macau University of Science and Technology, and Professor Zhang Kang from Guangzhou National Laboratory, the study identified HG9-91-01 as a RIPK3 inhibitor with significant neuroprotective properties.
“AI provides reliable tools and methods for drug discovery, such as virtual screening, quantitative structure-activity relationship modeling and de novo drug design,” Gao said in a news release, highlighting AI’s transformative potential in medical research.
Glaucoma, a progressive eye disorder characterized by fluid buildup, can lead to blindness if left untreated. The disease affects millions globally, with estimates predicting that 111.8 million people will suffer from it by 2040. While treatments exist to manage ocular hypertension, a definitive cure remains elusive.
Retinal ganglion cells (RGCs), which transmit visual signals from the eyes to the brain, are critically damaged in glaucoma, leading to optic nerve degradation. The study leveraged AI algorithms, including a large language model and graph neural network models, to identify molecules that target RIPK3, a key signaling molecule in necroptosis — a type of programmed cell death.
The researchers conducted extensive testing, utilizing models such as DynamicBind and in silico analysis of absorption, distribution, metabolism, excretion and toxicity (ADMET). Their findings revealed HG9-91-01 as the most promising candidate, confirmed through molecular simulations and biological experiments.
In a significant outcome, RGCs treated with HG9-91-01 showed higher survival rates under experimental conditions mimicking optic nerve damage, outperforming other candidates.
“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 mentioned,” Kang said in the news release. “In this study, we investigated potential drug treatments targeting RIPK3 to prevent RGC death and explored their role in preventing PANoptosis.”
Animal trials further validated HG9-91-01’s efficacy, showing that it prevented retinal thinning and reduced activation of molecules associated with various forms of cell death. These results indicate the compound’s potential in preventing PANoptosis, suggesting a new therapeutic avenue for glaucoma.
“AI technologies are useful for handling computationally intensive tasks and making rational decisions based on complex multimodal knowledge. However, possible concerns such as data privacy, transparency and bias should be addressed with caution,” Gao added, underscoring the balanced approach required in AI-driven research.
The research team plans to conduct further assessments to confirm HG9-91-01’s protective effects on retinal structure in patients with acute ocular hypertension. This AI-driven breakthrough heralds a promising future for glaucoma treatment, offering hope to millions affected by this debilitating disease.