A reference-based multi-lattice indexing method integrating prior information correction and iterative refinement in protein crystallography.

A new multi-lattice indexing method based on the principle of whole-pattern matching given cell dimensions and space-group symmetry is presented for macromolecular crystallography. The proposed method, termed the multi-crystal data processing suite (MCDPS), features a local correction for prior information accompanied by iterative refinement of experimental parameters, both of which are numerically and experimentally demonstrated to be critical for accurately identifying multiple crystal lattices. Further analysis of data reduction and structure determination with conventional single-crystal programs reveals that the processed multi-lattice data sets are comparable in quality to typical single-crystal ones in terms of crystallographic metrics. Importantly, it is confirmed that careful exclusion of overlapping reflections prior to scaling is necessary to guarantee an accurate data reduction result. The potential for multi-lattice indexing in solving the general macroscopic twinning problem is also explored.