Small-angle X-ray scattering (SAXS) has become a streamline method to characterize biological macromolecules, from small peptides to supramolecular complexes, in near-native solutions. Modern SAXS requires limited amounts of purified material, without the need for labelling, crystallization, or freezing. Dedicated beamlines at modern synchrotron sources yield high-quality data within or below several milliseconds of exposure time and are highly automated, allowing for rapid structural screening under different solutions and ambient conditions but also for time-resolved studies of biological processes. The advanced data analysis methods allow one to meaningfully interpret the scattering data from monodisperse systems, from transient complexes as well as flexible and heterogeneous systems in terms of structural models. Especially powerful are hybrid approaches utilizing SAXS with high-resolution structural techniques, but also with biochemical, biophysical, and computational methods. Here, we review the recent developments in the experimental SAXS practice and in analysis methods with a specific focus on the joint use of SAXS with complementary methods.
Model Reconstruction from Small-Angle X-Ray Scattering Data Using Deep Learning Methods
