Extending the resolution and phase-quality limits in automated model building with iterative refinement

Previously, the direct use of prior phase information from a single-wavelength anomalous diffraction (SAD) experiment with a multivariate likelihood function applied to automated model building with iterative refinement has been proposed [Skubak et al. (2004), Acta Cryst. D60, 2196-2201]. In this approach, the anomalous information from the experimental data is used in refinement to derive phase information in a maximum-likelihood formalism and provided a more theoretically valid way of incorporating prior phase information compared with current approaches. In the present work, the SAD multivariate likelihood function that directly uses prior phase information is tested against currently used functions on many different SAD data sets which exhibit a wide range of resolution limits and anomalous signal. The results clearly show the importance of the more theoretically valid utilization of prior phase information: the SAD function extends the resolution and phase-quality limits needed for successful automated model building with iterative refinement. Indeed, the multivariate likelihood function reduces the overfitting in the refinement procedure and performs consistently better than the current refinement targets in terms of the quality of the models obtained and the number of residues built.