Macromolecular crystallography is an iterative process. Rarely do the first crystals provide all the necessary data to solve the biological problem being studied. Each step benefits from experience learned in previous steps. To monitor the progress, the HKL package provides two tools: (i) Statistics, both weighted (χ2) and unweighted (R-merge), are provided. The Bayesian reasoning and multicomponent error model facilitates the obtaining of proper error estimates; and (ii) visualization of the process plays a double role: it helps the operator to confirm that the process of data reduction, including the resulting statistics, is correct, and it allows one to evaluate problems for which there are no good statistical criteria. Visualization also provides confidence that the point of diminishing returns in data collection and reduction has been reached. At that point the effort should be directed to solving the structure. The methods presented here have been applied to solve a large variety of problems, from inorganic molecules with 5 Å unit cell to rotavirus of 700 Å diameter crystallized in 700 x 1000 x 1400 Å cell. Overall quality of the method has been tested by many researchers by successful application of the programs to MAD structure determinations.
ASJC Scopus subject areas
- Molecular Biology