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Research
Progress Update: Unlocking the Secrets of Biological Molecules
Since its release in 2020, AlphaFold has revolutionized how proteins and their interactions are understood. Google DeepMind and Isomorphic Labs have been working together to build the foundations of a more powerful AI model that expands coverage beyond just proteins to the full range of biologically-relevant molecules.
Today we’re sharing an update on progress towards the next generation of AlphaFold. Our latest model can now generate predictions for nearly all molecules in the Protein Data Bank (PDB), frequently reaching atomic accuracy.
It unlocks new understanding and significantly improves accuracy in multiple key biomolecule classes, including ligands (small molecules), proteins, nucleic acids (DNA and RNA), and those containing post-translational modifications (PTMs). These different structure types and complexes are essential for understanding the biological mechanisms within the cell, and have been challenging to predict with high accuracy.
The model’s expanded capabilities and performance can help accelerate biomedical breakthroughs and realize the next era of ‘digital biology’ — giving new insights into the functioning of disease pathways, genomics, biorenewable materials, plant immunity, potential therapeutic targets, mechanisms for drug design, and new platforms for enabling protein engineering and synthetic biology.
Series of predicted structures compared to ground truth (white) from our latest AlphaFold model.
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