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1.  Evaluation of macromolecular electron-density map quality using the correlation of local r.m.s. density 
The correlation of local r.m.s. density is shown to be a good measure of the presence of distinct solvent and macromolecule regions in macromolecular electron-density maps.
It has recently been shown that the standard deviation of local r.m.s. electron density is a good indicator of the presence of distinct regions of solvent and protein in macromolecular electron-density maps [Terwilliger & Berendzen (1999 ▶). Acta Cryst. D55, 501–505]. Here, it is demonstrated that a complementary measure, the correlation of local r.m.s. density in adjacent regions on the unit cell, is also a good measure of the presence of distinct solvent and protein regions. The correlation of local r.m.s. density is essentially a measure of how contiguous the solvent (and protein) regions are in the electron-density map. This statistic can be calculated in real space or in reciprocal space and has potential uses in evaluation of heavy-atom solutions in the MIR and MAD methods as well as for evaluation of trial phase sets in ab initio phasing procedures.
doi:10.1107/S090744499901029X
PMCID: PMC2745882  PMID: 10531485
electron-density maps; local r.m.s. density
2.  Automated MAD and MIR structure solution 
A fully automated procedure for solving MIR and MAD structures has been developed using a scoring scheme to convert the structure-solution process into an optimization problem.
Obtaining an electron-density map from X-ray diffraction data can be difficult and time-consuming even after the data have been collected, largely because MIR and MAD structure determinations currently require many subjective evaluations of the qualities of trial heavy-atom partial structures before a correct heavy-atom solution is obtained. A set of criteria for evaluating the quality of heavy-atom partial solutions in macromolecular crystallography have been developed. These have allowed the conversion of the crystal structure-solution process into an optimization problem and have allowed its automation. The SOLVE software has been used to solve MAD data sets with as many as 52 selenium sites in the asymmetric unit. The automated structure-solution process developed is a major step towards the fully automated structure-determination, model-building and refinement procedure which is needed for genomic scale structure determinations.
doi:10.1107/S0907444999000839
PMCID: PMC2746121  PMID: 10089316
MAD; MIR; automated structure solution
3.  Discrimination of solvent from protein regions in native Fouriers as a means of evaluating heavy-atom solutions in the MIR and MAD methods 
The presence of distinct regions of high and low density variation in electron-density maps is found to be a good indicator of the correctness of a heavy-atom solution in the MIR and MAD methods.
An automated examination of the native Fourier is tested as a means of evaluation of a heavy-atom solution in MAD and MIR methods for macromolecular crystallography. It is found that the presence of distinct regions of high and low density variation in electron-density maps is a good indicator of the correctness of a heavy-atom solution in the MIR and MAD methods. The method can be used to evaluate heavy-atom solutions during MAD and MIR structure solutions and to determine the handedness of the structure if anomalous data have been measured.
doi:10.1107/S0907444998012657
PMCID: PMC2746120  PMID: 10089362
MAD; solvent discrimination

Results 1-3 (3)