20 December 2024
Biomolecules | Interview with Prof. Dr. Benoit Coulombe, Section Editor-in-Chief of Section “Biomacromolecules: Proteins”
We reached out to Prof. Dr. Benoit Coulombe, Editor-in-Chief of the Section “Biomacromolecules: Proteins”, to hear his thoughts on this year’s Nobel Prize and its impact on the scientific community and the publishing landscape.
Half of the 2024 Nobel Prize in chemistry was awarded to Demis Hassabis and John Jumper for their work on protein structure prediction, mainly through the development of the software AlphaFold. The other half of the prize was awarded to David Baker for his computational protein design work.
1. How do you see the 2024 Nobel Prize in chemistry, awarded for advances in AlphaFold's protein structure prediction, impacting the field of protein research?
It is rather rare that a Nobel Prize is awarded only a few years after a discovery or invention has been made. The first version of the software AlphaFold was launched in 2018, and the Nobel was awarded only 6 years later in 2024. In my opinion, this short “incubation period” demonstrates the importance of AlphaFold. This adds to the fact that the main Nature paper describing AlphaFold has been cited more than 20,000 times.
2. What are the current limitations of this discovery, and what improvements do you anticipate in the coming years?
Since the launch of the first version, two additional versions have been created. AlphaFold 2 in 2020 and AlphaFold 3 in 2024. The design of AlphaFold 2 is significantly different from AlphaFold 1 and the database is much larger, allowing a clear gain in performance. AlphaFold 3 is not limited to single chain proteins but can also predict the structure of protein complexes associated with RNA, DNA, ligands, ions and post-translational modifications (PTMs). In both cases, we witnessed important improvements. There is no doubt that additional improvements will be integrated in the coming years, paralleling the increasing power of computers. For example, AlphaFold protein modeling does not include most post-translational modifications, and its modeling of mutations is not yet robust. These points can be improved.
3. What are some of the most exciting recent developments in protein science that you believe deserve more attention?
Improvement in protein structure prediction, through AlphaFold, represents a quantum leap in protein science. Previous structure prediction software was largely inferior and the winning performance of AlphaFold at the competition Critical Assessment of Techniques for Protein Structure Prediction (CASP) is a reflection of this. Another aspect of protein science that deserves attention is Single-Cell Proteomics as this method allows us to illuminate the cell heterogeneity that takes place in organs and tissues, which has an important regulatory function. New generation mass spectrometers from different vendors will greatly accelerate Single-Cell Proteomics’ development.
4. As a Section Editor-in-Chief, how do you plan to shape “Biomacromolecules: Proteins” Section to include more research related to AI-based protein structure prediction?
As the development of AI tools progressively revolutionizes protein science, these tools will also reshape the Section “Biomacromolecules: Proteins”. I suppose this will be the case for other high-end journals. I predict that papers combining single-cell proteomics and AI will be more frequent in the coming years, leading to major advances in protein science.
5. Can you share any upcoming Special Issues or initiatives in the Biomolecules journal that focus on protein research and why authors should submit their work here?
We work hard to keep Biomolecules at the leading edge of research dealing with proteins with various initiatives such as Special Issues and thematic meetings. This is a good reason for researchers to submit their papers to Biomolecules.
