scholarly journals ATSAS 3.0: expanded functionality and new tools for small-angle scattering data analysis

2021 ◽  
Vol 54 (1) ◽  
Author(s):  
Karen Manalastas-Cantos ◽  
Petr V. Konarev ◽  
Nelly R. Hajizadeh ◽  
Alexey G. Kikhney ◽  
Maxim V. Petoukhov ◽  
...  
Keyword(s):  
Distribution Function ◽  
Small Angle ◽  
Small Angle Scattering ◽  
Distance Distribution ◽  
Scattering Data ◽  
Mode Analysis ◽  
Distance Distribution Function ◽  
Search Volume ◽  
Angle Scattering ◽  
Pair Distance Distribution Function

The ATSAS software suite encompasses a number of programs for the processing, visualization, analysis and modelling of small-angle scattering data, with a focus on the data measured from biological macromolecules. Here, new developments in the ATSAS 3.0 package are described. They include IMSIM, for simulating isotropic 2D scattering patterns; IMOP, to perform operations on 2D images and masks; DATRESAMPLE, a method for variance estimation of structural invariants through parametric resampling; DATFT, which computes the pair distance distribution function by a direct Fourier transform of the scattering data; PDDFFIT, to compute the scattering data from a pair distance distribution function, allowing comparison with the experimental data; a new module in DATMW for Bayesian consensus-based concentration-independent molecular weight estimation; DATMIF, an ab initio shape analysis method that optimizes the search model directly against the scattering data; DAMEMB, an application to set up the initial search volume for multiphase modelling of membrane proteins; ELLLIP, to perform quasi-atomistic modelling of liposomes with elliptical shapes; NMATOR, which models conformational changes in nucleic acid structures through normal mode analysis in torsion angle space; DAMMIX, which reconstructs the shape of an unknown intermediate in an evolving system; and LIPMIX and BILMIX, for modelling multilamellar and asymmetric lipid vesicles, respectively. In addition, technical updates were deployed to facilitate maintainability of the package, which include porting the PRIMUS graphical interface to Qt5, updating SASpy – a PyMOL plugin to run a subset of ATSAS tools – to be both Python 2 and 3 compatible, and adding utilities to facilitate mmCIF compatibility in future ATSAS releases. All these features are implemented in ATSAS 3.0, freely available for academic users at https://www.embl-hamburg.de/biosaxs/software.html.

scholarly journals SASPDF: pair distribution function analysis of nanoparticle assemblies from small-angle scattering data

2020 ◽  
Vol 53 (3) ◽  
pp. 699-709 ◽  
Author(s):  
Chia-Hao Liu ◽  
Eric M. Janke ◽  
Ruipen Li ◽  
Pavol Juhás ◽  
Oleg Gang ◽  
...  
Keyword(s):  
Distribution Function ◽  
Small Angle ◽  
Pair Distribution Function ◽  
Function Analysis ◽  
Small Angle Scattering ◽  
Scattering Data ◽  
Nanoparticle Assemblies ◽  
Angle Scattering ◽  
Pdf Analysis ◽  
Crystallite Sizes

SASPDF, a method for characterizing the structure of nanoparticle assemblies (NPAs), is presented. The method is an extension of the atomic pair distribution function (PDF) analysis to the small-angle scattering (SAS) regime. The PDFgetS3 software package for computing the PDF from SAS data is also presented. An application of the SASPDF method to characterize structures of representative NPA samples with different levels of structural order is then demonstrated. The SASPDF method quantitatively yields information such as structure, disorder and crystallite sizes of ordered NPA samples. The method was also used to successfully model the data from a disordered NPA sample. The SASPDF method offers the possibility of more quantitative characterizations of NPA structures for a wide class of samples.

Bayesian estimation of hyperparameters for indirect Fourier transformation in small-angle scattering

2000 ◽  
Vol 33 (6) ◽  
pp. 1415-1421 ◽  
Author(s):  
Steen Hansen
Keyword(s):  
Bayesian Methods ◽  
Small Angle ◽  
Fourier Transformation ◽  
Posterior Probability ◽  
Small Angle Scattering ◽  
Scattering Data ◽  
Distance Distribution Function ◽  
Posterior Probability Distribution ◽  
Angle Scattering ◽  
Real Experimental Data

Bayesian analysis is applied to the problem of estimation of hyperparameters, which are necessary for indirect Fourier transformation of small-angle scattering data. The hyperparameters most frequently needed are the overall noise level of the experiment and the maximum dimension of the scatterer. Bayesian methods allow the posterior probability distribution for the hyperparameters to be determined, making it possible to calculate the distance distribution function of interest as the weighted mean of all possible solutions to the indirect transformation problem. Consequently no choice of hyperparameters has to be made. The applicability of the method is demonstrated using simulated as well as real experimental data.

scholarly journals DAMMIF, a program for rapidab-initioshape determination in small-angle scattering

2009 ◽  
Vol 42 (2) ◽  
pp. 342-346 ◽  
Author(s):  
Daniel Franke ◽  
Dmitri I. Svergun
Keyword(s):  
Small Angle ◽  
Particle Shape ◽  
Small Angle Scattering ◽  
Binary Form ◽  
Scattering Data ◽  
Search Volume ◽  
Angle Scattering ◽  
Shape Determination ◽  
Equivalent Conditions

DAMMIF, a revised implementation of theab-initioshape-determination programDAMMINfor small-angle scattering data, is presented. The program was fully rewritten, and its algorithm was optimized for speed of execution and modified to avoid limitations due to the finite search volume. Symmetry and anisometry constraints can be imposed on the particle shape, similar toDAMMIN. In equivalent conditions,DAMMIFis 25–40 times faster thanDAMMINon a single CPU. The possibility to utilize multiple CPUs is added toDAMMIF. The application is available in binary form for major platforms.

Interpretation of small-angle scattering data of inhomogeneous ellipsoids

2004 ◽  
Vol 37 (5) ◽  
pp. 815-822 ◽  
Author(s):  
Gerhard Fritz ◽  
Alexander Bergmann
Keyword(s):  
Cross Sections ◽  
Small Angle ◽  
Theoretical Calculations ◽  
Negative Contrast ◽  
Small Angle Scattering ◽  
Distribution Functions ◽  
Distance Distribution ◽  
Scattering Data ◽  
Elliptical Cross ◽  
Angle Scattering

Small-angle scattering data of inhomogeneous ellipsoidal particles are discussed in terms of their pair distance distribution functionsp(r). Special attention is given to the determination of core and shell thicknesses and axis ratios as well as to large distances within the particles, since cross terms between parts of positive and negative contrast within the particle can produce misleading results, similar to homogeneous particles or Janus particles. Cross-section pair distance distribution functionspc(r) of cylinders with elliptical cross sections show similar behaviour. Theoretical calculations are compared with small-angle X-ray and neutron scattering (SAXS and SANS) data of cetyltrimethylammonium bromide in aqueous KCl solutions.

scholarly journals ATSAS 2.8: a comprehensive data analysis suite for small-angle scattering from macromolecular solutions

2017 ◽  
Vol 50 (4) ◽  
pp. 1212-1225 ◽  
Author(s):  
D. Franke ◽  
M. V. Petoukhov ◽  
P. V. Konarev ◽  
A. Panjkovich ◽  
A. Tuukkanen ◽  
...  
Keyword(s):  
Experimental Data ◽  
High Resolution ◽  
Ab Initio ◽  
Small Angle ◽  
Small Angle Scattering ◽  
Size Exclusion ◽  
Scattering Data ◽  
Mode Analysis ◽  
Angle Scattering ◽  
High Resolution Models

ATSASis a comprehensive software suite for the analysis of small-angle scattering data from dilute solutions of biological macromolecules or nanoparticles. It contains applications for primary data processing and assessment,ab initiobead modelling, and model validation, as well as methods for the analysis of flexibility and mixtures. In addition, approaches are supported that utilize information from X-ray crystallography, nuclear magnetic resonance spectroscopy or atomistic homology modelling to construct hybrid models based on the scattering data. This article summarizes the progress made during the 2.5–2.8ATSASrelease series and highlights the latest developments. These includeAMBIMETER, an assessment of the reconstruction ambiguity of experimental data;DATCLASS, a multiclass shape classification based on experimental data;SASRES, for estimating the resolution ofab initiomodel reconstructions;CHROMIXS, a convenient interface to analyse in-line size exclusion chromatography data;SHANUM, to evaluate the useful angular range in measured data;SREFLEX, to refine available high-resolution models using normal mode analysis;SUPALMfor a rapid superposition of low- and high-resolution models; andSASPy, theATSASplugin for interactive modelling inPyMOL. All these features and other improvements are included in theATSASrelease 2.8, freely available for academic users from https://www.embl-hamburg.de/biosaxs/software.html.

Irena: tool suite for modeling and analysis of small-angle scattering

2009 ◽  
Vol 42 (2) ◽  
pp. 347-353 ◽  
Author(s):  
Jan Ilavsky ◽  
Peter R. Jemian
Keyword(s):  
Small Angle ◽  
Materials Science ◽  
Small Angle Scattering ◽  
Scattering Data ◽  
Polymer Science ◽  
Modeling And Analysis ◽  
X Ray ◽  
Angle Scattering ◽  
Pair Distance Distribution Function ◽  
Dilute Limit

Irena, a tool suite for analysis of both X-ray and neutron small-angle scattering (SAS) data within the commercialIgor Proapplication, brings together a comprehensive suite of tools useful for investigations in materials science, physics, chemistry, polymer science and other fields. In addition to Guinier and Porod fits, the suite combines a variety of advanced SAS data evaluation tools for the modeling of size distribution in the dilute limit using maximum entropy and other methods, dilute limit small-angle scattering from multiple non-interacting populations of scatterers, the pair-distance distribution function, a unified fit, the Debye–Bueche model, the reflectivity (X-ray and neutron) using Parratt's formalism, and small-angle diffraction. There are also a number of support tools, such as a data import/export tool supporting a broad sampling of common data formats, a data modification tool, a presentation-quality graphics tool optimized for small-angle scattering data, and a neutron and X-ray scattering contrast calculator. These tools are brought together into one suite with consistent interfaces and functionality. The suite allows robust automated note recording and saving of parameters during export.

scholarly journals 2017 publication guidelines for structural modelling of small-angle scattering data from biomolecules in solution: an update

2017 ◽  
Vol 73 (9) ◽  
pp. 710-728 ◽  
Author(s):  
Jill Trewhella ◽  
Anthony P. Duff ◽  
Dominique Durand ◽  
Frank Gabel ◽  
J. Mitchell Guss ◽  
...  
Keyword(s):  
Small Angle ◽  
Task Force ◽  
Data Bank ◽  
Small Angle Scattering ◽  
Scattering Data ◽  
Quality Data ◽  
Angle Scattering ◽  
Publication Guidelines ◽  
Guidelines And Recommendations

In 2012, preliminary guidelines were published addressing sample quality, data acquisition and reduction, presentation of scattering data and validation, and modelling for biomolecular small-angle scattering (SAS) experiments. Biomolecular SAS has since continued to grow and authors have increasingly adopted the preliminary guidelines. In parallel, integrative/hybrid determination of biomolecular structures is a rapidly growing field that is expanding the scope of structural biology. For SAS to contribute maximally to this field, it is essential to ensure open access to the information required for evaluation of the quality of SAS samples and data, as well as the validity of SAS-based structural models. To this end, the preliminary guidelines for data presentation in a publication are reviewed and updated, and the deposition of data and associated models in a public archive is recommended. These guidelines and recommendations have been prepared in consultation with the members of the International Union of Crystallography (IUCr) Small-Angle Scattering and Journals Commissions, the Worldwide Protein Data Bank (wwPDB) Small-Angle Scattering Validation Task Force and additional experts in the field.

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