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  "notes": "The chart shows the exponential growth of cryo-EM structures in the Protein Data Bank (PDBe) over time, segmented by resolution.",
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      "text": "Combining AI-driven computational predictions of structure (e.g. AlphaFold) with cryo-EM experiments will be key to unravel protein-protein interactions, which mediate biological function.",
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      "text": "For structure-guided drug discovery, we need protein structures at ~2.5 Å resolution or better (i.e. near-atomic resolution).\nCryo-EM enables structure determination of dynamic protein complexes.\nCryo-EM structures at ~ 2 Å resolution were first reported by Sriram Subramaniam in 2015-2016, and the field has grown rapidly with >200 high-resolution structures projected for 2021.\nCombining AI-driven computational predictions of structure (e.g. AlphaFold) with cryo-EM experiments will be key to unravel protein-protein interactions, which mediate biological function.",
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      "text": "Cryogenic electron microscopy (cryo-EM) empirically determines the structure of macromolecules at near atomic-resolution without the need for their crystallisation. Cryo-EM involves shooting electron beams at a flash-frozen sample of protein or molecule of interest. The microscope generates images of these molecules that are then combined to reconstruct its 3D structure. All stages of the cryo-EM workflow are amenable to AI, ranging from specimen preparation and data collection to structure determination and atomic interpretation.",
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