Hugh Duffy

Mr. Ippolito 

AP Biology

1/14/2021

Briggs, Helen. “One of Biology's Biggest Mysteries 'Largely Solved' by AI.” BBC News, BBC, 30 Nov. 2020, www.bbc.com/news/science-environment-55133972. 

Recently, an A.I. called AlphaFold accomplished something that was previously thought to be impossible. In labs, mapping proteins can be a long, painful process. This generally takes years to complete, and requires manual labor. With AlphaFold technology, the A.I. can map proteins at speeds far faster than humans. AlphaFold is so smart, that it actually teaches itself how to better map proteins, while mapping proteins. It is comparable to Tesla auto-driving vehicles, which collect data while driving autonomously. This data is sent to the headquarters, where the algorithm is adjusted and automatically updated. With this same technology being applied to scientific research, specifically biology, medicine can develop at rates we’ve never seen before. In the case of AlphaFold, being able to map a protein is just a day and can help scientists rapidly develop vaccines. Additionally, this mapping technology can help scientists develop artificial proteins, which would help those who have protein deficiencies. Mapping proteins can be extremely useful when fighting against new infectious diseases like Covid-19. “One example is Covid-19, where scientists have been studying how the spike protein on the surface of the Sars-CoV-2 virus interacts with receptors in human cells.” (Briggs 2)

I thought this article was well written, however it felt rushed and lacking in information. There really wasn’t anything that explained how AlphaFold was developed, or how it maps proteins to begin with. This article would have benefitted from more extensive research. Briggs mentions how scientists have yet to study how AlphaFold interacts with proteins that have bonded to other macromolecules, so this could be a possibility as to why the article lacks information. The technology is just too new. Overall, this article was very intriguing, and poses the question of what the future holds for A.I. in biology.