Topia’s first repurposed drug study for Alzheimer

A critical area we focus on is Alzheimer’s Disease (AD), the most prevalent form of dementia affecting millions worldwide. With cases expected to surge in the coming decades, AD poses a growing public health crisis that requires ground-breaking solutions. Current treatments primarily address symptoms like memory loss and cognitive decline but do little to halt the disease’s relentless progression. The absence of a definitive cure and the limited effectiveness of existing therapies underscores the need for a novel approach. This is where AI steps in.

Tackling the Root Causes: Neuroinflammation and Neurochemical Imbalances

Growing scientific research indicates that chronic brain inflammation, known as neuroinflammation, and neurochemical imbalances significantly contribute to Alzheimer’s Disease (AD). Neurons, the brain’s communication cells, suffer damage and dysfunction, while protein deposits such as amyloid plaques and tau tangles accumulate, severely impacting brain function.

Neuroinflammation, a chronic state of inflammation in the brain, is believed to be a key factor in AD. Normally, immune cells like microglia clean up debris, but these cells become overactive in AD. This overactivity releases harmful molecules that damage neurons and disrupt their communication. The inflammatory response further fuels the buildup of protein plaques and tangles, hallmark AD features that accelerate the disease’s progression.

Additionally, a neurotransmitter acetylcholine (ACh) disruption is implicated in AD. ACh is crucial for memory and learning, but its levels decline due to the increased activity of enzymes like acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE). This decline impairs communication between brain cells, leading to memory loss, cognitive decline, and other AD symptoms.

By targeting both inflammation and ACh deficiency with a single drug, we aim to provide dual protection against AD progression. Reducing inflammation creates a more supportive environment for neuronal survival and function, while increasing ACh levels improves communication between brain cells, potentially enhancing cognitive function and memory.

Based on this hypothesis, we initiated a study to explore the interaction between an anti-inflammatory drug and BuChE. This virtual screening process involves analyzing extensive libraries of potential drug molecules to evaluate their predicted interactions with our target. This allows us to identify a shortlist of promising candidates with high docking scores, indicating strong potential for binding to the target molecule. From an initial pool of hundreds or even thousands of candidates, the virtual screening process rapidly narrows the field, leading us to select a few drugs with the most promising characteristics.

Our Promising Inhibitor: A Familiar Molecule with New Potential

Our research team employed advanced computational techniques to simulate the interaction between a potential anti-inflammatory drug candidate and a key brain enzyme involved in preventing Alzheimer’s Disease (AD). We virtually docked our repurposed drug candidate onto the structure of butyrylcholinesterase (BuChE), obtained from a protein database, and conducted a detailed analysis of these interactions.

To establish a benchmark, we also docked Rivastigmine, a known Alzheimer’s medication, with BuChE. This comparison allowed us to identify critical regions (active sites) on the enzyme essential for its function. Remarkably, both our repurposed drug candidate and Rivastigmine interacted with similar amino acids on BuChE through various bonds. These interactions, combined with a better docking score than the current therapy, suggest that our repurposed drug candidate could potentially inhibit BuChE activity, leading to increased acetylcholine (ACh) levels and improved cognitive function in Alzheimer’s patients.

Promising Initial Results and the Path Forward: Verification and Ongoing Research

Building on the promising results from our docking simulations, we confirmed our molecule’s binding affinity to BuChE through in vitro IC₅₀ determination. IC₅₀ is a scientific measure indicating the concentration of a drug needed to inhibit 50% of its target’s activity, with lower IC₅₀ values signifying higher potency.

Our in vitro experiments, utilizing a colorimetric assay to measure enzyme activity, demonstrated that our repurposed molecule can selectively inhibit BuChE at concentrations similar to standard Alzheimer’s drugs. This significant finding marks an important milestone, but it is just the beginning. We must conduct further in vivo studies to evaluate the drug’s ability to cross the blood-brain barrier (BBB) and its efficacy in animal models of Alzheimer’s Disease. This rigorous testing is crucial before considering human trials. Nevertheless, these initial results, achieved through AI-powered drug discovery, are highly encouraging.

The Future of AI in Drug Discovery: Hope for Alzheimer’s Patients

Our research highlights how AI is transforming drug discovery, showcasing its potential to revolutionize the field. By analyzing vast datasets, identifying complex patterns, and performing sophisticated simulations, AI is speeding up the development of new, effective treatments. We believe that AI-powered drug discovery holds tremendous promise for addressing Alzheimer’s Disease and other intricate neurological conditions. This technology offers hope to millions of patients and their families, paving the way for a future where Alzheimer’s is a treatable condition rather than a life sentence.

We are dedicated to advancing AI-driven drug discovery, continuously improving our methods and expanding our capabilities. Our ultimate goal is to provide safe, effective, and affordable treatments to those who need them most. The fight against Alzheimer’s continues, but with AI on our side, we are closer than ever to a brighter future.