At Topia, we're utilizing the immense power of Artificial Intelligence (AI) to revolutionize drug discovery. Our team is a unique force, a synergistic blend of cheminformatics experts who can navigate the intricate world of molecules, bioinformatics specialists who understand the language of life itself, IT professionals who ensure the seamless operation of our computational engines, and scientists from various disciplines who bring their diverse expertise to bear on the greatest challenges in human health. We are all passionately dedicated to developing effective and affordable treatments for diseases with critical unmet needs.
One such area of critical need is Alzheimer's Disease (AD), the most common form of dementia impacting millions globally. With projections for a substantial rise in coming decades, AD presents a growing public health crisis demanding innovative solutions. Current medications primarily manage symptoms, such as memory loss and cognitive decline, offering little to slow the relentless progression of the disease. The lack of a definitive cure and limited treatment efficacy highlight the urgency for a new approach. This is where AI-powered drug discovery steps in, offering a beacon of hope for millions struggling with AD.
Mounting scientific evidence suggests that neuroinflammation, chronic low-grade inflammation in the brain, and neurochemical imbalances play a significant role in AD. Neurons, the brain's communication cells, become damaged and dysfunctional, while protein deposits like amyloid plaques and tau tangles accumulate, wreaking havoc on brain function.
Chronic inflammation in the brain, called neuroinflammation, is a suspected culprit in AD. Immune cells like microglia, normally tasked with cleaning up debris, become overactive in AD. This overdrive leads to the release of harmful molecules that damage neurons and disrupt communication between them. The buildup of protein plaques and tangles, hallmarks of AD, is further fueled by this inflammatory response, accelerating the disease's progression.
In Alzheimer's Disease, a disturbance in the neurotransmitter is implicated. Neurotransmitter plays a vital role in memory and learning. When neurotransmitter levels decline, it disrupts communication between brain cells, contributing to memory loss, cognitive decline, and other hallmarks of AD.
By addressing both inflammation and neurotransmitter deficiency by single drug, we can achieve dual protection against AD progression as reduced inflammation creates a more favorable environment for neuronal survival and function and increased ACh levels enhance communication between brain cells, potentially improving cognitive function and memory.
With this hypothesis we initiated virtual screening process. We analysed vast libraries of potential drug molecules, evaluating their predicted interactions with our target. This allows us to identified a shortlist of promising candidates with high docking scores, indicating a strong potential for binding to the target molecule. From an initial pool of perhaps hundreds or even thousands of candidates, this virtual screening process rapidly narrow the field and few drugs with the most promising characteristics have been selected.
Our research team utilized highly advanced computational methods to simulate how a potential drug candidate interacts with a key enzyme in the brain for prevention of AD. In our study, we virtually dock our repurpose drug candidate onto the structure of target protein retrieved from a protein database. We then analyzed these interactions in detail.
For comparison, a known Alzheimer's medication, Rivastigmine, was also docked with target protein. This allowed us to identify the key regions (active sites) on the enzyme critical for its function. Interestingly, both our repurpose drug candidate and Rivastigmine interact with similar amino acids on target protein through various bonds. These interactions as well as better docking score then current therapeutic suggest that repurpose drug candidate potentially inhibit target protein activity, and increased neurotransmitter level and improved cognitive function in Alzheimer's patients.
Following the promising results from our docking simulations, we confirmed the molecule's binding affinity to target protein via in vitro IC₅₀ determination. IC₅₀ is a scientific measure used to determine the concentration of a drug required to inhibit 50% of its target's activity. The lower the IC₅₀, the more potent the drug.
Our in vitro experiments have revealed that our repurpose molecule can selectively inhibit target protein at concentrations comparable to standard AD drugs. This is a significant finding, but it's just the first step, there's still a long road ahead. We need to conduct further in vivo studies to assess the repurpose drug ability to cross BBB (blood brain barrier) and efficacy in animal models of AD. This rigorous testing process is essential before considering human trials. However, the initial results using AI-powered drug discovery are encouraging.
Our work is just one example of how AI is revolutionizing drug discovery. AI's ability to analyze vast datasets, identify intricate patterns, and perform complex simulations is accelerating the development of new and effective treatments. We believe that AI-powered drug discovery holds immense potential for tackling Alzheimer's Disease and other complex neurological conditions. It offers a beacon of hope for millions of patients and their families, paving the way for a future where Alzheimer's is not a sentence, but a treatable disease.
We are relentlessly pursuing advancements in AI-driven drug discovery, constantly refining our methods and expanding our capabilities. Our ultimate goal is to deliver safe, effective, and affordable treatments to those who need them most. The fight against Alzheimer's continues, but with the power of AI on our side, we are closer than ever to a brighter tomorrow.