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Superposition of Macromolecular Electron‐Density Maps in X‐ray Solution Scattering (SAXS)
Author(s) -
Nguyen Nhan D,
Grant Thomas D
Publication year - 2019
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.2019.33.1_supplement.779.27
Subject(s) - small angle x ray scattering , scattering , superposition principle , interpolation (computer graphics) , macromolecule , algorithm , resolution (logic) , extrapolation , computer science , physics , biological system , computational physics , chemistry , optics , mathematics , artificial intelligence , mathematical analysis , biology , quantum mechanics , image (mathematics) , biochemistry
Understanding the structure of biological macromolecules is important for determining their functions and cellular activities. With the growth of computational techniques in crystallography, X‐ray Solution Scattering Data (SAXS) becomes more applicable to reconstruct a wide range of 3D biomolecular structures from a low‐resolution profile by its easier use and simpler sample preparation. A novel program called (DENsity from Solution Scattering) resolves these disadvantages of low‐resolution data and retrieves 3D structural information of the complexes in solution. Due to containing the lack of information of 1D scattering data, these SAXS profiles require more modeling procedures and novel iterative algorithm to retrieve desired macromolecular structures. Our lab's previous publication on Nature elucidates the modeling algorithm using the Fast Fourier Transform to calculate and reconstruct 3D electron density maps of each profile. To obtain better 3D maps of macromolecules, we face another challenge of averaging method. The averaging step involves principal axis alignment, enantiomer selection, overlap score optimization among multiple (20) electron density maps. The updated version has been worked out by minimizing interpolation overuse and independently running with new Python codes that no longer require heavy EMAN2 installation as previous for the reconstruction purpose. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .