The real winner of Nobel in chemistry is AI

The world was astonished on Wednesday when half of the Nobel Prize in chemistry went to US scientist David Baker for "computational protein design" and the other half to Demis Hassabis and John M. Jumper in London for "protein structure prediction".

There is no disputing the fact that they have made amazing breakthroughs. The Nobel Prize committee remarked that "they cracked the code for proteins' amazing structures". What rallied global attention is the fact that both Hassabis and Jumper come from Google DeepMind, which specializes in artificial intelligence, and they created an AI model that fundamentally changes the way to study a protein's structure.

Given that even the Nobel Prize for physics went to computer scientists associated with AI, AI has been dominating the Nobel Prize this year, with someone even joking if AI was used in deciding the winners.

It's notable that the AI model Hassabis and Jumper developed is central to understanding the structure of proteins, in which amino acids are linked together in long chains and then fold in a manner that plays a decisive role in its functioning. Since the 1970s, researchers have been trying to predict protein structures from their amino acid sequences so as to gain a deeper understanding of their functions, for which they even launched Critical Assessment of Structure Prediction, which conducts community experiments in this regard.

For long the accuracy rate of predictions was just about 40 percent, far below the required 90 percent. It was not until Hassabis and Jumper developed the AI model AlphaFold that the rate reached 60 percent, which has since got better with AlphaFold2.

By understanding the three-dimensional structure of a protein, scientists can infer its role and how it interacts with other molecules, helping study diseases and develop new drugs. Besides, predicting protein structures helps in better comprehending the origins of life, which is linked to the Nobel Prize in physiology that went to researches in mRNA.

All these date back to Hassabis and Jumper's AlphaFold model developed decades ago. Clearly, AI has helped mankind by making endless computations a cakewalk, in the process hastening studies of the protein structure. The scientists who developed it deserve the prize as more scientists will now be encouraged to study it.