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Title: Accurate optimization of amino acid form factors for computing small-angle X-ray scattering intensity of atomistic protein structures

Abstract

Structure modellingviasmall-angle X-ray scattering (SAXS) data generally requires intensive computations of scattering intensity from any given biomolecular structure, where the accurate evaluation of SAXS profiles using coarse-grained (CG) methods is vital to improve computational efficiency. To date, most CG SAXS computing methods have been based on a single-bead-per-residue approximation but have neglected structural correlations between amino acids. To improve the accuracy of scattering calculations, accurate CG form factors of amino acids are now derived using a rigorous optimization strategy, termed electron-density matching (EDM), to best fit electron-density distributions of protein structures. This EDM method is compared with and tested against other CG SAXS computing methods, and the resulting CG SAXS profiles from EDM agree better with all-atom theoretical SAXS data. By including the protein hydration shell represented by explicit CG water molecules and the correction of protein excluded volume, the developed CG form factors also reproduce the selected experimental SAXS profiles with very small deviations. Taken together, these EDM-derived CG form factors present an accurate and efficient computational approach for SAXS computing, especially when higher molecular details (represented by theqrange of the SAXS data) become necessary for effective structure modelling.

Authors:
; ;
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States). Advanced Photon Source (APS)
Sponsoring Org.:
FOREIGN
OSTI Identifier:
1352231
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Applied Crystallography (Online); Journal Volume: 49; Journal Issue: 4
Country of Publication:
United States
Language:
ENGLISH

Citation Formats

Tong, Dudu, Yang, Sichun, and Lu, Lanyuan. Accurate optimization of amino acid form factors for computing small-angle X-ray scattering intensity of atomistic protein structures. United States: N. p., 2016. Web. doi:10.1107/S1600576716007962.
Tong, Dudu, Yang, Sichun, & Lu, Lanyuan. Accurate optimization of amino acid form factors for computing small-angle X-ray scattering intensity of atomistic protein structures. United States. doi:10.1107/S1600576716007962.
Tong, Dudu, Yang, Sichun, and Lu, Lanyuan. 2016. "Accurate optimization of amino acid form factors for computing small-angle X-ray scattering intensity of atomistic protein structures". United States. doi:10.1107/S1600576716007962.
@article{osti_1352231,
title = {Accurate optimization of amino acid form factors for computing small-angle X-ray scattering intensity of atomistic protein structures},
author = {Tong, Dudu and Yang, Sichun and Lu, Lanyuan},
abstractNote = {Structure modellingviasmall-angle X-ray scattering (SAXS) data generally requires intensive computations of scattering intensity from any given biomolecular structure, where the accurate evaluation of SAXS profiles using coarse-grained (CG) methods is vital to improve computational efficiency. To date, most CG SAXS computing methods have been based on a single-bead-per-residue approximation but have neglected structural correlations between amino acids. To improve the accuracy of scattering calculations, accurate CG form factors of amino acids are now derived using a rigorous optimization strategy, termed electron-density matching (EDM), to best fit electron-density distributions of protein structures. This EDM method is compared with and tested against other CG SAXS computing methods, and the resulting CG SAXS profiles from EDM agree better with all-atom theoretical SAXS data. By including the protein hydration shell represented by explicit CG water molecules and the correction of protein excluded volume, the developed CG form factors also reproduce the selected experimental SAXS profiles with very small deviations. Taken together, these EDM-derived CG form factors present an accurate and efficient computational approach for SAXS computing, especially when higher molecular details (represented by theqrange of the SAXS data) become necessary for effective structure modelling.},
doi = {10.1107/S1600576716007962},
journal = {Journal of Applied Crystallography (Online)},
number = 4,
volume = 49,
place = {United States},
year = 2016,
month = 6
}
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