title: Can I solve my structure by SAD phasing? Planning an experiment, scaling data and evaluating the useful anomalous correlation and anomalous signal.
abstract: A key challenge in the SAD phasing method is solving a structure when the anomalous signal-to-noise ratio is low. Here, algorithms and tools for evaluating and optimizing the useful anomalous correlation and the anomalous signal in a SAD experiment are described. A simple theoretical framework [Terwilliger et al. (2016), Acta Cryst. D72, 346-358] is used to develop methods for planning a SAD experiment, scaling SAD data sets and estimating the useful anomalous correlation and anomalous signal in a SAD data set. The phenix.plan_sad_experiment tool uses a database of solved and unsolved SAD data sets and the expected characteristics of a SAD data set to estimate the probability that the anomalous substructure will be found in the SAD experiment and the expected map quality that would be obtained if the substructure were found. The phenix.scale_and_merge tool scales unmerged SAD data from one or more crystals using local scaling and optimizes the anomalous signal by identifying the systematic differences among data sets, and the phenix.anomalous_signal tool estimates the useful anomalous correlation and anomalous signal after collecting SAD data and estimates the probability that the data set can be solved and the likely figure of merit of phasing.
authors.affiliation: Bioscience Division, Los Alamos National Laboratory, Mail Stop M888, Los Alamos, NM 87545, USA.
authors.forename: Thomas C
authors.initials: TC
authors.lastname: Terwilliger
authors.affiliation: Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research, Wellcome Trust/MRC Building, Cambridge CB2 0XY, England.
authors.forename: Gábor
authors.initials: G
authors.lastname: Bunkóczi
authors.affiliation: Physics Division, Los Alamos National Laboratory, Mail Stop D454, Los Alamos, NM 87545, USA.
authors.forename: Li Wei
authors.initials: LW
authors.lastname: Hung
authors.affiliation: Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
authors.forename: Peter H
authors.initials: PH
authors.lastname: Zwart
authors.affiliation: Life Sciences Institute, University of Michigan, Ann Arbor, MI 48109, USA.
authors.forename: Janet L
authors.initials: JL
authors.lastname: Smith
authors.affiliation: Life Sciences Institute, University of Michigan, Ann Arbor, MI 48109, USA.
authors.forename: David L
authors.initials: DL
authors.lastname: Akey
authors.affiliation: Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
authors.forename: Paul D
authors.initials: PD
authors.lastname: Adams
mesh_terms: D000465:Algorithms; D018360:Crystallography, X-Ray / Q000379:methods*; D011336:Probability; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D059629:Signal-To-Noise Ratio
chemical_list: D011506:Proteins
keywords: SAD phasing; anomalous signal; experimental design