title: Towards a black-box for biological EXAFS data analysis. II. Automatic BioXAS Refinement and Analysis (ABRA).
abstract: In biological systems, X-ray absorption spectroscopy (XAS) can determine structural details of metal binding sites with high resolution. Here a method enabling an automated analysis of the corresponding EXAFS data is presented, utilizing in addition to least-squares refinement the prior knowledge about structural details and important fit parameters. A metal binding motif is characterized by the type of donor atoms and their bond lengths. These fit results are compared by bond valance sum analysis and target distances with established structures of metal binding sites. Other parameters such as the Debye-Waller factor and shift of the Fermi energy provide further insights into the quality of a fit. The introduction of mathematical criteria, their combination and calibration allows an automated analysis of XAS data as demonstrated for a number of examples. This presents a starting point for future applications to all kinds of systems studied by XAS and allows the algorithm to be transferred to data analysis in other fields.
authors.affiliation: EMBL Hamburg, c/o DESY, Notkestrasse 85, 22603 Hamburg, Germany.
authors.forename: Gerd
authors.initials: G
authors.lastname: Wellenreuther
authors.forename: Venkataraman
authors.initials: V
authors.lastname: Parthasarathy
authors.forename: Wolfram
authors.initials: W
authors.lastname: Meyer-Klaucke
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D001704:Biopolymers / Q000737:chemistry*; D008667:Metalloproteins / Q000737:chemistry*; D008670:Metals / Q000737:chemistry*; D011485:Protein Binding; D056928:X-Ray Absorption Spectroscopy / Q000379:methods*
chemical_list: D001704:Biopolymers; D008667:Metalloproteins; D008670:Metals