UC San Francisco Researchers Utilize Google DeepMind's AlphaFold to Map Autism-Related Protein Interactions
Researchers at the University of California, San Francisco (UCSF) have created a molecular atlas detailing over a thousand interactions between proteins derived from genes associated with autism. This groundbreaking work, published in the journal Science, aims to clarify how gene mutations contribute to profound autism. The team, led by Nevan Krogan and Dr. Matthew State, utilized Google DeepMind's AI system, AlphaFold, to identify direct protein-to-protein contacts within lab-grown cells. This application of AI significantly accelerated the research process, allowing insights that previously took years to be gained in a matter of hours. The study involved selecting 100 proteins from high-risk autism genes, injecting them into cells, and then analyzing the additional proteins that attached to them. Subsequently, they introduced mutations found in patients with profound autism to observe the resulting changes in protein interactions, conducting these experiments in frogs and brain organoids. 
