Automatic protein structure solution from weak X-ray data

Abstract

Determining new protein structures from X-ray diffraction data at low resolution or with a weak anomalous signal is a difficult and often an impossible task. Here we propose a multivariate algorithm that simultaneously combines the structure determination steps. In tests on over 140 real data sets from the protein data bank, we show that this combined approach can automatically build models where current algorithms fail, including an anisotropically diffracting 3.88 Å RNA polymerase II data set. The method seamlessly automates the process, is ideal for non-specialists and provides a mathematical framework for successfully combining various sources of information in image processing. X-ray crystallography is a routine technique used to solve protein structures, but is often limited by weak anomalous scattering signals and low-resolution data. Here, the authors develop a synergistic algorithm to significantly increase the success rate of structure solution when the signal is weak.