BCL::SAXS: GPU accelerated Debye method for computation of small angle X-ray scattering profiles
ABSTRACT Small angle X‐ray scattering (SAXS) is an experimental technique used for structural characterization of macromolecules in solution. Here, we introduce BCL::SAXS—an algorithm designed to replicate SAXS profiles from rigid protein models at different levels of detail. We first show our deriv...
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Published in | Proteins, structure, function, and bioinformatics Vol. 83; no. 8; pp. 1500 - 1512 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Blackwell Publishing Ltd
01.08.2015
Wiley Subscription Services, Inc Wiley |
Subjects | |
Online Access | Get full text |
ISSN | 0887-3585 1097-0134 |
DOI | 10.1002/prot.24838 |
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Summary: | ABSTRACT
Small angle X‐ray scattering (SAXS) is an experimental technique used for structural characterization of macromolecules in solution. Here, we introduce BCL::SAXS—an algorithm designed to replicate SAXS profiles from rigid protein models at different levels of detail. We first show our derivation of BCL::SAXS and compare our results with the experimental scattering profile of hen egg white lysozyme. Using this protein we show how to generate SAXS profiles representing: (1) complete models, (2) models with approximated side chain coordinates, and (3) models with approximated side chain and loop region coordinates. We evaluated the ability of SAXS profiles to identify a correct protein topology from a non‐redundant benchmark set of proteins. We find that complete SAXS profiles can be used to identify the correct protein by receiver operating characteristic (ROC) analysis with an area under the curve (AUC) > 99%. We show how our approximation of loop coordinates between secondary structure elements improves protein recognition by SAχS for protein models without loop regions and side chains. Agreement with SAXS data is a necessary but not sufficient condition for structure determination. We conclude that experimental SAXS data can be used as a filter to exclude protein models with large structural differences from the native. Proteins 2015; 83:1500–1512. © 2015 Wiley Periodicals, Inc. |
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Bibliography: | NSF - No. Career 0742762 and OIA 0959454 NIH - No. R01 GM080403, R01 MH090192, and R01 GM099842 ArticleID:PROT24838 NLM (to D.K.P.) - No. 5T15LM007450-09 istex:07DDF0AA47FE5F78A8E522CBC03505A5D68EF356 ark:/67375/WNG-QC2KSSJZ-D ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 USDOE USDOE Office of Science National Science Foundation (NSF) None |
ISSN: | 0887-3585 1097-0134 |
DOI: | 10.1002/prot.24838 |