Se lleva mucho tiempo so\u00f1ando con comprender y dominar por completo las herramientas qu\u00edmicas de la vida: las prote\u00ednas. Demis Hassabis y John M. Jumper han utilizado con \u00e9xito la inteligencia artificial para predecir la estructura de casi todas las prote\u00ednas conocidas. David Baker ha aprendido a dominar los componentes b\u00e1sicos de la vida y a crear prote\u00ednas completamente nuevas. El potencial de sus descubrimientos es enorme.<\/p>\n
The diversity of life testifies to proteins\u2019 amazing capacity as chemical tools. They control and drive all the chemi\u00adcal reactions that together are the basis of life. Proteins also function as hormones, signal substances, antibodies and the building blocks of different tissues.<\/p>\n
\u201cOne of the discoveries being recognised this year concerns the construction of spectacular proteins. The other is about fulfilling a 50-year-old dream: predicting protein structures from their amino acid sequences. Both of these discoveries open up vast possibilities,\u201d says Heiner Linke, Chair of the Nobel Committee for Chemistry.<\/p>\n
Proteins generally consist of 20 different amino acids, which can be described as life\u2019s building blocks. In 2003,\u00a0David Baker<\/strong>\u00a0succeeded in using these blocks to design a new protein that was unlike any other protein. Since then, his research group has produced one imaginative protein creation after another, including proteins that can be used as pharmaceuticals, vaccines, nanomaterials and tiny sensors.<\/p>\n The second discovery concerns the prediction of protein structures. In proteins, amino acids are linked together in long strings that fold up to make a three-dimensional structure, which is decisive for the protein\u2019s function. Since the 1970s, researchers had tried to predict protein structures from amino acid sequences, but this was notoriously difficult. However, four years ago, there was a stunning breakthrough.<\/p>\n In 2020,\u00a0Demis Hassabis<\/strong>\u00a0and\u00a0John Jumper<\/strong>\u00a0presented an AI model called AlphaFold2. With its help, they have been able to predict the structure of virtually all the 200 million proteins that researchers have identified. Since their breakthrough, AlphaFold2 has been used by more than two million people from 190 countries. Among a myriad of scientific applications, researchers can now better understand antibiotic resistance and create images of enzymes that can decompose plastic.<\/p>\n Life could not exist without proteins. That we can now predict protein structures and design our own proteins confers the greatest benefit to humankind.<\/p>\n