Breakthroughs honoured: 2024 Nobel Prizes
As part of the 2024 Nobel Prize Week, the prestigious awards have been presented. These include the Nobel Prize in Medicine or Physiology for the discoverers of microRNAs as a new class of regulatory molecules, and the Nobel Prize in Chemistry for AI-supported methods in protein design and the rapid calculation of their structures.
The Nobel Prizes stem from the foundation established by Swedish entrepreneur and inventor of dynamite, Alfred -Nobel, and include a certificate, a medal, and a monetary award of 11 million Swedish kronor (approximately €950,000). The prizes have been presented by King Carl XVI Gustaf of Sweden in the Stockholm Concert Hall on December 10, the anniversary of Nobel’s death. First awarded in 1901, this year marks the 115th occasion.
The ceremony during the Nobel Prize Week is accompanied by concerts, art exhibitions, and the Nobel lectures given by the laureates. Among the speakers are the US researchers Victor Ambros and Gary Ruvkun, who are awarded the Nobel Prize in Medicine or Physiology for their discovery of microRNA, as well as David Baker, Demis Hassabis, and John M. Jumper, who share the Nobel Prize in Chemistry for their work on computational protein design and AI-driven predictions of protein folding from amino acid sequences.
MicroRNA – a therapeutic target
The Nobel Assembly at the Karolinska Institute in Stockholm has honoured groundbreaking basic research with this year’s Nobel Prize in Medicine or Physiology, which are already influencing clinical drug development. In their laudatory address, the jury described the discovery of the first regulatory microRNAs carried out by developmental biologist Victor Ambros (71, University of Massachusetts Medical School, Worcester) and geneticist Gary Ruvkun (72, Massachusetts General Hospital and Harvard Medical School, Boston) as a “new dimension of gene regulation”. Today, microRNAs represent promising therapeutic targets for conditions such as heart failure, cancer, and metabolic disorders.
Rewriting Gene Regulation
The discovery of microRNAs challenged the prevailing belief at the time that genes could only be regulated by proteins. At the time, both Ambros and Ruvkun were postdoctoral researchers in the laboratory of Nobel laureate Robert Horvitz at the Massachusetts Institute of Technology (MIT), studying two mutated genes in the nematode Caenorhabditis elegans. Ambros demonstrated that the lin-4 gene inhibits the activity of lin-14 and does not code for a protein, but rather a microRNA that is just 22 nucleotides long. As Ruvkun found, this microRNA binds to the lin-14 mRNA through an antisense mechanism, blocking its translation. Their 1993 findings were initially met with little attention, but this changed with the discovery of the highly conserved microRNA let-7 in Ruvkun’s lab. It was soon clear that this newly discovered universal mechanism had been in existence for over 500 million years in all multicellular organisms.
The advent of AI
The Nobel Prize in Chemistry has also been deemed groundbreaking by the Nobel Committee of the Royal Swedish Academy of Sciences. It marks a milestone in the rapid adoption of Artificial Intelligence in research and drug development. David Baker (62, University of Washington and Howard Hughes Medical Institute) enabled the rapid and reliable prediction of protein structures using AI algorithms, providing an alternative to time-consuming methods like X-ray crystallography. His Rosetta algorithm could predict 3D protein structures that were previously known. By having the software predict the appropriate amino acid sequence for a desired structure, Baker was able to design an entirely new range of proteins. The freely available version, Rosetta@home, theoretically allows anyone to become a protein designer. The de novo design of proteins, enhanced by AI, enables nearly unlimited new creations – including the development of innovative therapies.
Protein folding 2.0
The foundation for the accurate prediction of protein folding was laid by British scientist Demis Hassabis (48) and US researcher John M. Jumper (39) at Google DeepMind. Hassabis, a neuroscientist, chess player, and former video game developer, founded his own development studio and later DeepMind Technologies in London, which was acquired by Google Health for around $400 million in 2014. There, he trained the AI model AlphaFold using a vast protein database and, together with Jumper, developed the impressive successor AlphaFold2, which delivered protein structures with accuracy comparable to X-ray crystallography and was followed more recently by a third version. This breakthrough allowed the two AI researchers to predict the structure of all known single proteins.
Today, millions of users worldwide use the AI model, expanding the known range of protein structures. When combined with Baker’s research, AlphaFold even facilitates the simulation of protein interactions, paving the way for the design of biologics. These are already being commercialized by companies, heralding a new era in therapeutic development.
