AI is revolutionizing the treatment of glaucoma – the world’s second leading cause of blindness
AI identifies HG9-91-01 as a promising treatment for acute glaucoma, offering neuroprotection and preserving vision by targeting RIPK3.
Glaucoma, the second leading cause of blindness globally, affects millions and is projected to reach 111.8 million cases by 2040. This progressive eye disorder results from fluid buildup, increasing intraocular pressure (IOP) and damaging the optic nerve.
While treatments to lower IOP exist, they do not halt disease progression for all patients. Retinal ganglion cells (RGCs), which transmit visual signals from the eye to the brain, often succumb to degeneration, furthering optic nerve damage. This underscores the urgent need for neuroprotective therapies to complement pressure-lowering treatments.
Recent research highlights necroptosis, a type of programmed cell death, as a key factor in RGC loss. Published in the Chinese Medical Journal, necroptosis shares characteristics with apoptosis (natural cell breakdown) and necrosis (injury-related cell damage), and receptor-interacting protein kinase 3 (RIPK3) is central to this process.
Targeting RIPK3 could provide a novel approach to preserving RGCs and preventing further damage. Advances in artificial intelligence (AI) are paving the way for breakthroughs in identifying effective inhibitors for RIPK3, offering hope for patients with acute glaucoma.
AI has revolutionized drug discovery by streamlining processes and accelerating the identification of potential treatments. A research team employed advanced AI models, including large language models (LLMs) and graph neural network models, to identify compounds targeting RIPK3. Their findings detail how AI-driven approaches can uncover novel treatments for acute glaucoma.
Using AI tools like ChatGPT and DynamicBind, the researchers generated a list of small-molecule compounds likely to interact with RIPK3. These tools sorted candidate drugs based on predicted binding affinities, validated through molecular simulations and biological experiments.
Dr. Yuanxu Gao, one of the lead researchers, noted that “AI provides reliable tools and methods for drug discovery, such as virtual screening, quantitative structure-activity relationship modeling, and de novo drug design.”
Drug discovery has traditionally been a time-consuming and resource-intensive process, often taking years to identify viable therapeutic options. AI algorithms, by contrast, can analyze vast datasets in a fraction of the time.
Related Stories
In this study, researchers harnessed the power of AI to predict the interactions between small molecules and RIPK3, dramatically shortening the timeline for drug screening. This approach not only accelerates discovery but also reduces the costs associated with traditional drug development methods.
Among the candidates identified, HG9-91-01 emerged as the most promising inhibitor of RIPK3. Molecular simulations confirmed that HG9-91-01 forms a stable complex with RIPK3, outperforming other candidates in terms of binding affinity and safety profiles.
ADMET (absorption, distribution, metabolism, excretion, and toxicity) predictions further supported the compound’s suitability as a drug candidate.
The compound’s efficacy was validated in both in vitro and in vivo experiments. In laboratory tests mimicking optic nerve damage, RGCs exposed to oxygen-glucose deprivation (OGD) showed significantly higher survival rates when treated with HG9-91-01 compared to other candidates. Additionally, HG9-91-01 reduced markers of pyroptosis, a type of inflammatory cell death, demonstrating its role in mitigating RGC loss.
Prof. Zhang Kang, a co-author of the study, emphasized the innovative approach, stating, “Although numerous studies have focused on anti-apoptotic, anti-necroptotic, and anti-pyroptotic drugs for treating acute ocular hypertension, strategies targeting PANoptosis are rarely mentioned. This study explores potential drug treatments targeting RIPK3 to prevent RGC death and the cascade of cell death mechanisms.”
The innovative use of AI in this context highlights its transformative potential in modern medicine. By integrating computational methods with traditional laboratory techniques, the researchers achieved a level of precision and efficiency previously unattainable.
The ability of AI to predict drug efficacy and safety in silico ensures that only the most promising candidates proceed to experimental validation, thereby saving valuable resources.
In mouse models of acute glaucoma, HG9-91-01 exhibited neuroprotective effects by preserving retinal structure and preventing thinning—a common consequence of elevated IOP. The compound inhibited the activation of signaling molecules associated with apoptosis, pyroptosis, and necroptosis, collectively referred to as PANoptosis. By regulating these pathways, HG9-91-01 demonstrated its potential to protect the retina and preserve visual function.
Retinal thinning, a hallmark of glaucoma progression, directly correlates with the loss of visual acuity. The ability of HG9-91-01 to maintain retinal thickness suggests that it may slow or even halt the degenerative processes underlying glaucoma.
Additionally, its role in inhibiting PANoptosis underscores its potential as a multi-targeted therapeutic agent. Unlike treatments that focus solely on lowering IOP, HG9-91-01 addresses the root causes of RGC loss, offering a more comprehensive solution.
Further analysis revealed that HG9-91-01 regulates key proteins involved in cell death pathways, reducing the expression of markers associated with apoptosis, pyroptosis, and necroptosis. These findings provide valuable insights into the molecular mechanisms underlying its neuroprotective effects. By targeting multiple pathways simultaneously, HG9-91-01 represents a significant advancement in the treatment of neurodegenerative ocular diseases.
The study underscores the transformative potential of AI in drug development. By combining computational tools with biological validation, researchers can expedite the discovery of effective treatments. However, challenges such as data privacy, transparency, and bias must be addressed to ensure ethical and reliable applications of AI in medicine.
Dr. Gao highlighted the importance of further research, stating, “AI technologies are useful for handling computationally intensive tasks and making rational decisions based on complex multimodal knowledge. However, further confirmatory retinal assessments are needed to validate HG9-91-01’s effectiveness in protecting the retinal structure in patients with acute ocular hypertension.”
The implications of this research extend beyond glaucoma, showcasing the potential of AI-driven methodologies to address other neurodegenerative diseases. By refining these techniques, scientists can develop targeted therapies for a wide range of conditions, from Alzheimer’s to Parkinson’s disease. The integration of AI into biomedical research marks a new era of innovation, where data-driven approaches complement traditional scientific methods.
As researchers refine AI-driven drug discovery methods, the future of glaucoma treatment looks brighter. The identification of HG9-91-01 as a potential therapy exemplifies how cutting-edge technology and scientific ingenuity can address urgent medical challenges. By leveraging AI’s capabilities, scientists are not only accelerating drug development but also improving the outlook for patients at risk of vision loss.
Moreover, the collaborative nature of this research highlights the importance of interdisciplinary efforts in advancing medical science. By bringing together experts in AI, pharmacology, and ophthalmology, the team demonstrated how diverse perspectives can lead to groundbreaking discoveries. This approach sets a precedent for future research, emphasizing the value of collaboration in tackling complex health issues.
As the global burden of glaucoma continues to rise, the need for innovative treatments becomes increasingly urgent. AI-driven breakthroughs like HG9-91-01 offer a glimpse into a future where vision loss may no longer be an inevitable outcome for millions of patients.
Through continued research and collaboration, the dream of preventing blindness becomes ever more attainable.
Note: Materials provided above by The Brighter Side of News. Content may be edited for style and length.
Like these kind of feel good stories? Get The Brighter Side of News' newsletter.