Google DeepMind wins joint Nobel Prize in Chemistry for protein prediction AI

Hassabis and Jumper created AlphaFold, which in 2020 solved an issue scientists have been wrestling with for many years: predicting the three-dimensional construction of a protein from a sequence of amino acids. The AI device has since been used to predict the shapes of all proteins known to science.

Their newest mannequin, AlphaFold 3, can predict the structures of DNA, RNA, and molecules like ligands, that are important to drug discovery. DeepMind has additionally released the source code and database of its outcomes to scientists free of charge. 

Baker has created a number of AI instruments for designing and predicting the construction of proteins, comparable to a family of programs called Rosetta. In 2022, his lab created an open-source AI device known as ProteinMPNN that might assist researchers uncover beforehand unknown proteins and design totally new ones. It helps researchers who’ve an actual protein construction in thoughts discover amino acid sequences that fold into that form.

Most not too long ago, in late September, Baker’s lab introduced it had developed custom molecules that permit scientists to exactly goal and eradicate proteins related to illnesses in residing cells. 

“[Proteins] developed over the course of evolution to unravel the issues that organisms confronted throughout evolution. However we face new issues right this moment, like covid. If we might design proteins that have been nearly as good at fixing new issues as those that developed throughout evolution are at fixing previous issues, it could be actually, actually highly effective,” Baker advised MIT Technology Review in 2022.