Abstract

The positions of several water molecules can be determined in protein crystallography, either buried in internal cavities or at the protein surface. It is important to be able to estimate the expected number of these water molecules to facilitate crystal structure determination. Here, a multiple Poisson regression model implemented on nearly 10 000 protein crystal structures shows that the number of detectable water molecules depends on eight variables: crystallographic resolution, R factor, percentage of solvent in the crystal, average B factor of the protein atoms, percentage of amino acid residues in loops, average solvent-accessible surface area of the amino acid residues, grand average of hydropathy of the protein(s) in the asymmetric unit and normalized number of heteroatoms that are not water molecules. Furthermore, a secondary analysis tested the effect of different software packages. Given the values of these eight variables, it is possible to compute the expected number of water molecules detectable in electron-density maps with reasonable accuracy (as suggested by an external validation of the model).

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