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. 2022 Mar 8;119(10):e2202107119.
doi: 10.1073/pnas.2202107119. Epub 2022 Mar 2.

Researchers turn to deep learning to decode protein structures

Stephen Ornes

Researchers turn to deep learning to decode protein structures

Stephen Ornes. Proc Natl Acad Sci U S A. .

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No abstract available

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Figures

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AlphaFold uses AI to predict the shapes of proteins; structural biologists are using the program to deepen our understanding of the big molecules. This image shows AlphaFold's predicted structure (in magenta) of a glycoprotein found on the surface of a T cell. Researchers used other data to complete the structure (in cyan). Image credit: Reprinted with permission from Springer Nature: ref. .
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The revolution in structural biology isn’t attributable to AI alone; the algorithms have to train on big datasets of high-resolution crystal structures generated by technologies such as nuclear magnetic resonance spectroscopy or cryogenic electron microscopy (cryo-EM), which produced the above image of a protein complex called β-galactosidase. Image credit: Veronica Falconieri and Sriram Subramaniam (National Cancer Institute, Bethesda, MD).
See this image and copyright information in PMC

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