Abstract

Many macromolecular model-building and refinement programs can automatically place solvent atoms in electron density at moderate-to-high resolution. This process frequently builds water molecules in place of elemental ions, the identification of which must be performed manually. The solvent-picking algorithms in phenix.refine have been extended to build common ions based on an analysis of the chemical environment as well as physical properties such as occupancy, B factor and anomalous scattering. The method is most effective for heavier elements such as calcium and zinc, for which a majority of sites can be placed with few false positives in a diverse test set of structures. At atomic resolution, it is observed that it can also be possible to identify tightly bound sodium and magnesium ions. A number of challenges that contribute to the difficulty of completely automating the process of structure completion are discussed.

Highlights

  • In addition to organic molecules, macromolecular crystals frequently contain ordered monoatomic ions

  • The small regulatory protein calmodulin binds four Ca2+ ions, which act as a switch for calmodulin binding to other proteins; we selected the highest resolution structure in the Protein Data Bank (PDB) (PDB entry 1exr; Wilson & Brunger, 2000)

  • The false-positive rate was extremely low, with only two spurious Ca atoms built in PDB entries 3dzz and 3m83 (Levisson et al, 2012)

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Summary

Introduction

In addition to organic molecules, macromolecular crystals frequently contain ordered monoatomic ions. These ions often account for a nontrivial amount of the scattering density in the unit cell and are often physiologically relevant, aiding in catalysis and substrate binding as well as stabilizing protein folds (Glusker, 1991; Harding et al, 2010). They are common components in many crystallization solutions, often at high concentrations. Identification of the lighter elements such as sodium, magnesium or chlorine is problematic, especially

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