Researchers at the University of Cambridge have employed artificial intelligence to expedite the discovery of treatments for Parkinson’s disease by screening millions of compounds, ultimately identifying five potent candidates. This AI-driven method has enhanced the screening process tenfold and reduced costs drastically, potentially accelerating the development of new treatments for the rapidly growing global Parkinson’s population.
Proteins are responsible for important cell processes, but when people have Parkinson’s, these proteins go rogue and cause the death of nerve cells. When proteins misfold, they can form abnormal clusters called Lewy bodies, which build up within brain cells stopping them from functioning properly. While there are currently clinical trials for Parkinson’s currently underway, no disease-modifying drug has been approved, reflecting the inability to directly target the molecularThis has been a major obstacle in Parkinson’s research, because of the lack of methods to identify the correct molecular targets and engage with them. This technological gap has severely hampered the development of effective treatments.
“Instead of screening experimentally, we screen computationally,” said Vendruscolo, who is co-director of the Centre for Misfolding Diseases. “By using the knowledge we gained from the initial screening with our machine learning model, we were able to train the model to identify the specific regions on these small molecules responsible for binding, then we can re-screen and find more potent molecules.
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