Old fold in a new X-ray diffraction dataset? Low-resolution molecular replacement using representative structural templates can provide phase information.

Abstract

The advent of structural genomics has led to a dramatic increase in the number of structures deposited in the Protein Data Bank. The number of new folds, however, still remains a very small fraction of the total number of deposited structures. Recent data on the progress of the structural genomics initiative reveals that more than 85% of target proteins that progress to the stage of data collection and structure determination have a known fold. Enzymes, which tend to exploit reaction space while adopting a common stable scaffold, contribute significantly to this observation. Herein, we evaluate a method to examine the "old fold in a new dataset" scenario likely to be encountered in the structural genomics pipeline. We demonstrate that a fold detection strategy based on secondary structure signatures followed by molecular replacement using a minimalist model can be effectively used to solve the phase problem in X-ray crystallography without further recourse to heavy atom derivatives or multiple anomalous dispersion techniques. Three common folds-the triosephosphate isomerase (TIM), adenine nucleotide alpha hydrolase-like (HUP), and RNA recognition motif (RRM)-were examined using this approach. The results presented herein also provide an estimate of the extent of phase information that can be derived from a single domain in a large multidomain structure.