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[Translate to English:] © Jürgen Huhn​/​TU Dortmund
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Study Analyzes 400 Million Years of Enzyme Evolution

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A computer-generated model of a yeast fungus, consisting of red-yellow curls interspersed with molecular structures. © Charité​/​Markus Ralser
Three-dimensional shape of the yeast enzyme Erg11, generated by AlphaFold2. Erg11 is inhibited by azoles, a specific class of antifungal drugs. If Erg11 changes, the fungus can develop a tolerance to the drugs.
Enzymes accelerate chemical reactions in organisms – without them, life would not be possible. With the help of artificial intelligence (AI), researchers at Charité – Universitätsmedizin Berlin, one of the largest university hospitals in Europe, have now succeeded in analyzing the laws of their evolution on a large scale. In the journal Nature, they describe which parts of enzymes change comparatively quickly and which ones remain practically unchanged over time. These findings are important for the development of new antibiotics, for example. Professor Toni Goßmann from the Department of Biochemical and Chemical Engineering at TU Dortmund University also contributed to the paper.

The research team at Charité, led by Professor Markus Ralser, used AlphaFold2, an AI model whose developers from the US and the UK were awarded the Nobel Prize in Chemistry in 2024, and the Berzelius supercomputer in Sweden to examine the spatial development of enzymes in the course of evolution. The study focused on around 11,300 enzymes from 27 yeast species that have developed over 400 million years. Determining the 3D structure of enzymes by experimental means is very time-consuming, but by leveraging AlphaFold2 the researchers were able to calculate the shape of almost 10,000 enzymes within just a few months. Professor Toni Goßmann, head of the “Computational Systems Biology” group at Dortmund Life Science Center (DOLCE), contributed to the study. His task was to apply a method known as dN/dS analysis to the AI models of the enzymes calculated with AlphaFold2.

In Nature, the team presents clear patterns of enzyme evolution: The surfaces of the enzymes change much faster than their active centers, i.e., those sites where the actual chemical reaction takes place. These remain stable over a long period. Functionally relevant sites on the surface onto which other molecules bind mostly are preserved as well. These findings are not only important for understanding biological processes but are also of major significance for the development of new drugs. For example, it might be possible for antibiotics to target precisely these stable areas of the enzyme and in this way prevent resistance.

Article

Charité press release

Portrait photo of Toni Goßmann © S. Jonek​​/​​Universität Bielefeld
Professor Toni Goßmann is head of the Computational Systems Biology.

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