scholarly journals MARTINI bead form factors for the analysis of time-resolved X-ray scattering of proteins

2014 ◽  
Vol 47 (4) ◽  
pp. 1190-1198 ◽  
Author(s):  
Stephan Niebling ◽  
Alexander Björling ◽  
Sebastian Westenhoff
Keyword(s):  
Form Factors ◽  
Coarse Graining ◽  
Data Interpretation ◽  
Coarse Grained ◽  
Scattering Data ◽  
Structural Refinement ◽  
Time Resolved ◽  
X Ray ◽  
X Ray Scattering ◽  
Ray Scattering

Time-resolved small- and wide-angle X-ray scattering (SAXS and WAXS) methods probe the structural dynamics of proteins in solution. Although technologically advanced, these methods are in many cases limited by data interpretation. The calculation of X-ray scattering profiles is computationally demanding and poses a bottleneck for all SAXS/WAXS-assisted structural refinement and, in particular, for the analysis of time-resolved data. A way of speeding up these calculations is to represent biomolecules as collections of coarse-grained scatterers. Here, such coarse-graining schemes are presented and discussed and their accuracies examined. It is demonstrated that scattering factors coincident with the popular MARTINI coarse-graining scheme produce reliable difference scattering in the range 0 < q < 0.75 Å−1. The findings are promising for future attempts at X-ray scattering data analysis, and may help to bridge the gap between time-resolved experiments and their interpretation.

scholarly journals REGALS: a general method to deconvolve X-ray scattering data from evolving mixtures

2020 ◽  
Author(s):  
Steve P. Meisburger ◽  
Da Xu ◽  
Nozomi Ando
Keyword(s):  
A Priori ◽  
Scattering Data ◽  
Biological Macromolecules ◽  
Time Resolved ◽  
X Ray ◽  
X Ray Scattering ◽  
Open Source Software Package ◽  
Saxs Analysis ◽  
Structural Methods ◽  
Ray Scattering

AbstractMixtures of biological macromolecules are inherently difficult to study using structural methods, as increasing complexity presents new challenges for data analysis. Recently, there has been growing interest in studying evolving mixtures using small-angle X-ray scattering (SAXS) in conjunction with time-resolved, high-throughput, or chromatography-coupled setups. Deconvolution and interpretation of the resulting datasets, however, are nontrivial when neither the scattering components nor the way in which they evolve are known a priori. To address this issue, we introduce the REGALS method (REGularized Alternating Least Squares), which incorporates simple expectations about the data as prior knowledge and utilizes parameterization and regularization to provide robust deconvolution solutions. The restraints used by REGALS are general properties such as smoothness of profiles and maximum dimensions of species, which makes it well-suited for exploring datasets with unknown species. Here we apply REGALS to analyze experimental data from four types of SAXS experiment: anion-exchange (AEX) coupled SAXS, ligand titration, time-resolved mixing, and time-resolved temperature jump. Based on its performance with these challenging datasets, we anticipate that REGALS will be a valuable addition to the SAXS analysis toolkit and enable new experiments. The software is implemented in both MATLAB and python and is available freely as an open-source software package.

Prediction of protein structure with the coarse-grained UNRES force field assisted by small X-ray scattering data and knowledge-based information

2017 ◽  
Vol 86 ◽  
pp. 228-239 ◽  
Author(s):  
Agnieszka S. Karczyńska ◽  
Magdalena A. Mozolewska ◽  
Paweł Krupa ◽  
Artur Giełdoń ◽  
Adam Liwo ◽  
...  
Keyword(s):  
Protein Structure ◽  
Force Field ◽  
Coarse Grained ◽  
Scattering Data ◽  
X Ray ◽  
Knowledge Based ◽  
X Ray Scattering ◽  
Small X ◽  
Ray Scattering

scholarly journals MARTINI bead form factors for the analysis of time-resolved X-ray scattering of proteins. Erratum

2018 ◽  
Vol 51 (3) ◽  
pp. 968-968
Author(s):  
Stephan Niebling ◽  
Alexander Björling ◽  
Sebastian Westenhoff
Keyword(s):  
Form Factors ◽  
Typographical Error ◽  
Time Resolved ◽  
X Ray ◽  
X Ray Scattering ◽  
Ray Scattering

A typographical error in the article by Niebling, Björling & Westenhoff [J. Appl. Cryst. (2014), 47, 1190–1198] is corrected.

scholarly journals Biasing RNA coarse-grained folding simulations with Small--Angle X--ray Scattering (SAXS) data

2021 ◽  
Author(s):  
Liuba Mazzanti ◽  
Lina Alferkh ◽  
Elisa Frezza ◽  
Samuela Pasquali
Keyword(s):  
High Resolution ◽  
Small Angle ◽  
Conformational Space ◽  
Coarse Grained ◽  
Scattering Data ◽  
Saxs Data ◽  
X Ray ◽  
Rna Molecules ◽  
X Ray Scattering ◽  
Ray Scattering

RNA molecules can easily adopt alternative structures in response to different environmental conditions. As a result, a molecule's energy landscape is rough and can exhibits a multitude of deep basins. In the absence of a high-resolution structure, Small Angle X-ray Scattering data (SAXS) can narrow down the conformational space available to the molecule and be used in conjunction with physical modeling to obtain high-resolution putative structures to be further tested by experiments. Because of the low-resolution of this data, it is natural to implement the integration of SAXS data into simulations using a coarse-grained representation of the molecule, allowing for much wider searches and faster evaluation of SAXS theoretical intensity curves than with atomistic models. We present here the theoretical framework and the implementation of a simulation approach based on our coarse-grained model HiRE-RNA combined with SAXS evaluations "on-the-fly" leading the simulation toward conformations agreeing with the scattering data, starting from partially folded structures as the ones that can easily be obtained from secondary structures predictions based tools. We show on three benchmark systems how our approach can successfully achieve high-resolution structures with remarkable similarity with the native structure recovering not only the overall shape, as imposed by SAXS data, but also the details of initially missing base pairs.

scholarly journals REGALS: a general method to deconvolve X-ray scattering data from evolving mixtures

IUCrJ ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 225-237
Author(s):  
Steve P. Meisburger ◽  
Da Xu ◽  
Nozomi Ando
Keyword(s):  
A Priori ◽  
Scattering Data ◽  
Biological Macromolecules ◽  
Time Resolved ◽  
X Ray ◽  
X Ray Scattering ◽  
Open Source Software Package ◽  
Saxs Analysis ◽  
Structural Methods ◽  
Ray Scattering

Mixtures of biological macromolecules are inherently difficult to study using structural methods, as increasing complexity presents new challenges for data analysis. Recently, there has been growing interest in studying evolving mixtures using small-angle X-ray scattering (SAXS) in conjunction with time-resolved, high-throughput or chromatography-coupled setups. Deconvolution and interpretation of the resulting datasets, however, are nontrivial when neither the scattering components nor the way in which they evolve are known a priori. To address this issue, the REGALS method (regularized alternating least squares) is introduced, which incorporates simple expectations about the data as prior knowledge, and utilizes parameterization and regularization to provide robust deconvolution solutions. The restraints used by REGALS are general properties such as smoothness of profiles and maximum dimensions of species, making it well suited for exploring datasets with unknown species. Here, REGALS is applied to the analysis of experimental data from four types of SAXS experiment: anion-exchange (AEX) coupled SAXS, ligand titration, time-resolved mixing and time-resolved temperature jump. Based on its performance with these challenging datasets, it is anticipated that REGALS will be a valuable addition to the SAXS analysis toolkit and enable new experiments. The software is implemented in both MATLAB and Python and is available freely as an open-source software package.

Time-Resolved Measurements of Overlayer Ordering in Electrodeposition

1996 ◽  
Vol 451 ◽  
Author(s):  
A. C. Finnefrock ◽  
L. J. Bullert ◽  
K. L. Ringland ◽  
P. D. Tingi ◽  
H. D. Abruña ◽  
...  
Keyword(s):  
Scattering Data ◽  
Electrode Position ◽  
Initial Value ◽  
Time Resolved ◽  
X Ray ◽  
Surface Ordering ◽  
X Ray Scattering ◽  
Kinetics Of ◽  
Ray Scattering

ABSTRACTWe report in situ time-resolved surface x-ray scattering measurements of the underpoten-tial deposition of Cu2+ on Pt(111) in the presence of Cl− in HClO4 solution. Chronoamperometric (current vs. time) measurements indicate that after a potential step, the electrode-position current decays to 1/e of its initial value in at most 0.12 seconds. In contrast, our simultaneous time-resolved surface x-ray scattering data reveal that the overlayer requires on the order of two seconds to develop long-range periodic order. These results demonstrate that the kinetics of surface ordering can be significantly different from the kinetics of charge-transfer and illustrate the power of time-resolved surface x-ray scattering for in situ studies of electrodeposition.

scholarly journals Reconstructing three-dimensional shape envelopes from time-resolved small-angle X-ray scattering data

2008 ◽  
Vol 41 (6) ◽  
pp. 1046-1052 ◽  
Author(s):  
Jessica Lamb ◽  
Lisa Kwok ◽  
Xiangyun Qiu ◽  
Kurt Andresen ◽  
Hye Yoon Park ◽  
...  
Keyword(s):  
Conformational Changes ◽  
Small Angle ◽  
Three Dimensional ◽  
Model Systems ◽  
Scattering Data ◽  
Time Resolved ◽  
X Ray ◽  
X Ray Scattering ◽  
Group I ◽  
Ray Scattering

Modern computing power has made it possible to reconstruct low-resolution, three-dimensional shapes from solution small-angle X-ray scattering (SAXS) data on biomolecules withouta prioriknowledge of the structure. In conjunction with rapid mixing techniques, SAXS has been applied to time resolve conformational changes accompanying important biological processes, such as biomolecular folding. In response to the widespread interest in SAXS reconstructions, their value in conjunction with such time-resolved data has been examined. The group I intron fromTetrahymena thermophilaand its P4–P6 subdomain are ideal model systems for investigation owing to extensive previous studies, including crystal structures. The goal of this paper is to assay the quality of reconstructions from time-resolved data given the sacrifice in signal-to-noise required to obtain sharp time resolution.

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