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In the conventional histogram-matching technique for phase extension and refinement for proteins a simple one-to-one transformation is made in the protein region to modify calculated density so that it will have some target histogram in addition to solvent flattening. This work describes an investigation where the density modification takes into account not only the current calculated density at a grid point but also some characteristic of the environment of the grid point within some distance R. This characteristic can be one of the local maximum density, the local minimum density or the local variance of density. The grid points are divided into ten groups, each containing the same number of grid points, for ten different ranges of value of the local characteristic. The ten groups are modified to give different histograms, each corresponding to that obtained under the same circumstances from a structure similar to the one under investigation. This process is referred to as the double-histogram matching method. Other processes which have been investigated are the weighting of structure factors when calculating maps with estimated phases and also the use of a factor to dampen the change of density and so control the refinement process. Two protein structures were used in numerical trials, RNApl [Bezborodova, Ermekbaeva, Shlyapnikov, Polyakov & Bezborodov (1988). Biokhimiya, 53, 965-973] and 2-Zn insulin [Baker, Blundell, Cutfield, Cutfield, Dodson, Dodson, Hodgkin, Hubbard, lsaacs, Reynolds, Sakabe, Sakabe & Vijayan (1988). Philos. Trans. R. Soc. London Ser. B, 319, 456--469]. Comparison of the proposed procedures with the normal histogram-matching technique without structure-factor weighting or damping gives mean phase errors reduced by up to 10° with map correlation coefficients improved by as much as 0.14. Compared to the normal histogram used with weighting of structure factors and damping, the improvement due to the use of the double-histogram method is usually of order 4° in mean phase error and an increase of 0.06-0.08 in the map correlation coefficient. It is concluded that the most reliable results are found with the local-maximum condition and with R in the range 0.5-0.6 Å.
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