Browsing by Author "Miller, M. D."
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Item A deep learning solution for crystallographic structure determination(International Union of Crystallography, 2023) Pan, T.; Jin, S.; Miller, M. D.; Kyrillidis, A.; Phillips, G. N.The general de novo solution of the crystallographic phase problem is difficult and only possible under certain conditions. This paper develops an initial pathway to a deep learning neural network approach for the phase problem in protein crystallography, based on a synthetic dataset of small fragments derived from a large well curated subset of solved structures in the Protein Data Bank (PDB). In particular, electron-density estimates of simple artificial systems are produced directly from corresponding Patterson maps using a convolutional neural network architecture as a proof of concept.Item Structural characterization of DynU16, a START/Bet v1-like protein involved in dynemicin biosynthesis(International Union of Crystallography, 2021) Alvarado, S. K.; Miller, M. D.; Bhardwaj, M.; Thorson, J. S.; Van Lanen, S. G.; Phillips, G. N.The 1.5 Å resolution crystal structure of DynU16, a protein identified in the dynemicin-biosynthetic gene cluster, is reported. The structure adopts a di-domain helix-grip fold with a uniquely positioned open cavity connecting the domains. The elongated dimensions of the cavity appear to be compatible with the geometry of a linear polyene, suggesting the involvement of DynU16 in the upstream steps of dynemicin biosynthesis.