Solving protein structures by combining structure prediction, molecular replacement and direct-methods-aided model completion

Abstract

We propose a direct-methods-based dual-space iteration strategy for model completion of molecular replacement (MR) with predicted models. Direct methods has been demonstrated as a powerful tool for phase optimization in protein crystallography, whereas the dual-space iterative strategy is particularly suitable for solving crystallographic protein-complex structures starting from a small subunit. This combined approach provides a shortcut in simplifying the pre-processing steps of predicted models for MR and for final model completion.

Highly accurate protein structure prediction can generate accurate models of protein and protein–protein complexes in X-ray crystallography. However, the question of how to make more effective use of predicted models for completing structure analysis, and which strategies should be employed for the more challenging cases such as multi-helical structures, multimeric structures and extremely large structures, both in the model preparation and in the completion steps, remains open for discussion. In this paper, a new strategy is proposed based on the framework of direct methods and dual-space iteration, which can greatly simplify the pre-processing steps of predicted models both in normal and in challenging cases. Following this strategy, full-length models or the conservative structural domains could be used directly as the starting model, and the phase error and the model bias between the starting model and the real structure would be modified in the direct-methods-based dual-space iteration. Many challenging cases (from CASP14) have been tested for the general applicability of this constructive strategy, and almost complete models have been generated with reasonable statistics. The hybrid strategy therefore provides a meaningful scheme for X-ray structure determination using a predicted model as the starting point.