ArticleProteins2015
BCL::SAXS: GPU accelerated Debye method for computation of small angle X-ray scattering profiles.
Article in Proteins, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Hybrid methods for combined experimental and computational determination of protein structure.The Journal of chemical physics · 2020Review
- Integrating solvation shell structure in experimentally driven molecular dynamics using x-ray solution scattering data.The Journal of chemical physics · 2020Article
- Federating Structural Models and Data: Outcomes from A Workshop on Archiving Integrative Structures.Structure (London, England : 1993) · 2019Article
- Signaling through non-membrane nuclear phosphoinositide binding proteins in human health and disease.Journal of lipid research · 2019Review
- Rosetta Protein Structure Prediction from Hydroxyl Radical Protein Footprinting Mass Spectrometry Data.Analytical chemistry · 2018Article
- Iterative Molecular Dynamics-Rosetta Membrane Protein Structure Refinement Guided by Cryo-EM Densities.Journal of chemical theory and computation · 2017Article
- Article
- CASP11--An Evaluation of a Modular BCL::Fold-Based Protein Structure Prediction Pipeline.PloS one · 2016Article
Corrections and comments
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Authors and funding
5 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.