We have 2 papers published in @nature today!
One describes AlphaFold, which uses deep neural networks to predict protein structures with high accuracy. AlphaFold made the most accurate predictions at the 2018 scientific community assessment CASP13. 1/4https://deepmind.com/blog/article/AlphaFold-Using-AI-for-scientific-discovery …
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Proteins are the building blocks of biology. They start off as a string of amino acids that fold into intricate 3D structures. Knowing the 3D structure helps us understand their function, but predicting such structures is an unsolved question in science. 2/4pic.twitter.com/1meRwkYKFI
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Predicting how these chains will fold into the structure of a protein - the “protein folding problem” - is fundamental to understanding its role within the body and could one day enable scientists to target & design new, effective cures for diseases. 3/4
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While we’re excited by these results, there is still much more we need to understand. We’d like to thank the organisers of CASP13 & the experimentalists whose structures enabled the assessment & we look forward to taking this work forward with the protein folding community. 4/4
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