The study, published in the journal Nature Communications, marks a major step forward in the field of precision and personalized medicine, using advanced data technology to decipher the impact of genetic mutations on human health.
By combining AI-powered protein models with genome sequencing data, the team discovered why some proteins are more vulnerable to harmful mutations.
Specifically, the research team used advanced AI technology AlphaFold developed by Google DeepMind to analyze the impact of all possible mutations on all types of proteins in the human body.
“Evolution has created a protective mechanism for the most essential proteins, helping them avoid mutations that would destabilize their structure, while less important proteins do not seem to have the same resistance,” said Associate Professor Dan Andrews, who led the study.
The team from the John Curtin School of Medical Research and the ANU School of Computer Science also offers an explanation for why seemingly unimportant genes often play a large role in genetic diseases.
“It is important to pinpoint exactly which genetic system is disrupted in each individual, helping to guide the most appropriate treatment,” added Mr Andrews.
According to Associate Professor Andrews, the team's next goal is to develop an automated system that can recommend effective treatment for each individual, based on specific genetic and pathological data.
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