Bayesian machine learning improves single-wavelength anomalous diffraction phasing.

ABSTRACT: Single-wavelength X-ray anomalous diffraction (SAD) is a frequently employed technique to solve the phase problem in X-ray crystallography. The precision and accuracy of recovered anomalous differences are crucial for determining the correct phases. Continuous rotation (CR) and inverse-beam geometry (IBG) anomalous data collection methods have been performed on tetragonal lysozyme and monoclinic survivin crystals and analysis carried out of how correlated the pairs of Friedel's reflections are after scaling. A multivariate Bayesian model for estimating anomalous differences was tested, which takes into account the correlation between pairs of intensity observations and incorporates the a priori knowledge about the positivity of intensity. The CR and IBG data collection methods resulted in

SUBMITTER: Garcia-Bonete MJ 

PROVIDER: S-EPMC6833979 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature