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Title: Methods for SAXS-Based Structure Determination of Biomolecular Complexes

Measurements from small-angle X-ray scattering (SAXS) are highly informative to determine the structures of bimolecular complexes in solution. Here, we describe current and recent SAXS-driven developments, with an emphasis on computational modeling. In particular, accurate methods to computing one theoretical scattering profile from a given structure model are discussed, with a key focus on structure factor coarse-graining and hydration contribution. Methods for reconstructing topological structures from an experimental SAXS profile are currently under active development. We report on several modeling tools designed for conformation generation that make use of either atomic-level or coarse-grained representations. Furthermore, since large, flexible biomolecules can adopt multiple well-defined conformations, a traditional single-conformation SAXS analysis is inappropriate, so we also discuss recent methods that utilize the concept of ensemble optimization, weighing in on the SAXS contributions of a heterogeneous mixture of conformations. These tools will ultimately posit the usefulness of SAXS data beyond a simple space-filling approach by providing a reliable structure characterization of biomolecular complexes under physiological conditions.
Authors:
 [1]
  1. Case Western Reserve Univ., Cleveland, OH (United States). Center for Proteomics and Dept. of Pharmacology
Publication Date:
OSTI Identifier:
1165626
Grant/Contract Number:
AC02-06CH11357; AC02-98CH10886
Type:
Accepted Manuscript
Journal Name:
Advanced Materials
Additional Journal Information:
Journal Volume: 26; Journal Issue: 46; Journal ID: ISSN 0935-9648
Publisher:
Wiley
Research Org:
Argonne National Lab. (ANL), Argonne, IL (United States). Advanced Photon Source (APS)
Sponsoring Org:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22); US National Institutes of Health (NIH)
Country of Publication:
United States
Language:
ENGLISH
Subject:
59 BASIC BIOLOGICAL SCIENCES; computing; protein; DNA; RNA; ensemble optimization; biomolecular complexes