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 Guinier peak analysis for visual and automated inspection of small-angle X-ray scattering data

2016 ◽  
Vol 49 (5) ◽  
pp. 1412-1419 ◽  
Author(s):  
Christopher D. Putnam
Keyword(s):  
Small Angle ◽  
Peak Position ◽  
Scattering Data ◽  
Radius Of Gyration ◽  
Automated Inspection ◽  
Elongation Ratio ◽  
Saxs Data ◽  
X Ray ◽  
X Ray Scattering ◽  
Ray Scattering

The Guinier region in small-angle X-ray scattering (SAXS) defines the radius of gyration,Rg, and the forward scattering intensity,I(0). In Guinier peak analysis (GPA), the plot ofqI(q)versus q2transforms the Guinier region into a characteristic peak for visual and automated inspection of data. Deviations of the peak position from the theoretical position in dimensionless GPA plots can suggest parameter errors, problematic low-resolution data, some kinds of intermolecular interactions or elongated scatters. To facilitate automated analysis by GPA, the elongation ratio (ER), which is the ratio of the areas in the pair-distribution functionP(r) after and before theP(r) maximum, was characterized; symmetric samples have ER values around 1, and samples with ER values greater than 5 tend to be outliers in GPA analysis. Use of GPA+ER can be a helpful addition to SAXS data analysis pipelines.

scholarly journals A customizable software for fast reduction and analysis of large X-ray scattering data sets: applications of the newDPDAKpackage to small-angle X-ray scattering and grazing-incidence small-angle X-ray scattering

2014 ◽  
Vol 47 (5) ◽  
pp. 1797-1803 ◽  
Author(s):  
Gunthard Benecke ◽  
Wolfgang Wagermaier ◽  
Chenghao Li ◽  
Matthias Schwartzkopf ◽  
Gero Flucke ◽  
...  
Keyword(s):  
Small Angle ◽  
Data Reduction ◽  
Grazing Incidence ◽  
Scattering Data ◽  
Limiting Factor ◽  
Online Data ◽  
Saxs Data ◽  
X Ray ◽  
X Ray Scattering ◽  
Ray Scattering

X-ray scattering experiments at synchrotron sources are characterized by large and constantly increasing amounts of data. The great number of files generated during a synchrotron experiment is often a limiting factor in the analysis of the data, since appropriate software is rarely available to perform fast and tailored data processing. Furthermore, it is often necessary to perform online data reduction and analysis during the experiment in order to interactively optimize experimental design. This article presents an open-source software package developed to process large amounts of data from synchrotron scattering experiments. These data reduction processes involve calibration and correction of raw data, one- or two-dimensional integration, as well as fitting and further analysis of the data, including the extraction of certain parameters. The software,DPDAK(directly programmable data analysis kit), is based on a plug-in structure and allows individual extension in accordance with the requirements of the user. The article demonstrates the use ofDPDAKfor on- and offline analysis of scanning small-angle X-ray scattering (SAXS) data on biological samples and microfluidic systems, as well as for a comprehensive analysis of grazing-incidence SAXS data. In addition to a comparison with existing software packages, the structure ofDPDAKand the possibilities and limitations are discussed.

scholarly journals Obtaining tertiary protein structures by the ab-initio interpretation of small angle X-ray scattering data

2019 ◽  
Author(s):  
Christopher Prior ◽  
Owen R Davies ◽  
Daniel Bruce ◽  
Ehmke Pohl
Keyword(s):  
Ab Initio ◽  
Small Angle ◽  
Protein Structures ◽  
Scattering Data ◽  
Ab Initio Method ◽  
Primary Sequence ◽  
Saxs Data ◽  
X Ray ◽  
X Ray Scattering ◽  
Ray Scattering

ABSTRACTSmall angle X-ray scattering (SAXS) has become an important tool to investigate the structure of proteins in solution. In this paper we present a novel ab-initio method to represent polypeptide chains as discrete curves that can be used to derive a meaningful three-dimensional model from only the primary sequence and experimental SAXS data. High resolution crystal structures were used to generate probability density functions for each of the common secondary structural elements found in proteins. These are used to place realistic restraints on the model curve’s geometry. To evaluate the quality of potential models and demonstrate the efficacy of this novel technique we developed a new statistic to compare the entangled geometry of two open curves, based on mathematical techniques from knot theory. The chain model is coupled with a novel explicit hydration shell model in order derive physically meaningful 3D models by optimizing configurations against experimental SAXS data using a monte-caro based algorithm. We show that the combination of our ab-initio method with spatial restraints based on contact predictions successfully derives a biologically plausible model of the coiled–coil component of the human synaptonemal complex central element protein.SIGNIFICANCESmall-angle X-ray scattering allows for structure determination of biological macromolecules and their complexes in aqueous solution. Using a discrete curve representation of the polypeptide chain and combining it with empirically determined constraints and a realistic solvent model we are now able to derive realistic ab-initio 3-dimensional models from BioSAXS data. The method only require a primary sequence and the scattering data form the user.

scholarly journals Modeling the Structure of RNA Molecules with Small-Angle X-Ray Scattering Data

PLoS ONE ◽  
2013 ◽  
Vol 8 (11) ◽  
pp. e78007 ◽  
Author(s):  
Michal Jan Gajda ◽  
Denise Martinez Zapien ◽  
Emiko Uchikawa ◽  
Anne-Catherine Dock-Bregeon
Keyword(s):  
Small Angle ◽  
Scattering Data ◽  
X Ray ◽  
Rna Molecules ◽  
X Ray Scattering ◽  
Ray Scattering

scholarly journals The accurate assessment of small-angle X-ray scattering data

2015 ◽  
Vol 71 (1) ◽  
pp. 45-56 ◽  
Author(s):  
Thomas D. Grant ◽  
Joseph R. Luft ◽  
Lester G. Carter ◽  
Tsutomu Matsui ◽  
Thomas M. Weiss ◽  
...  
Keyword(s):  
Data Quality ◽  
Small Angle ◽  
Small Sample ◽  
Quality Analysis ◽  
Scattering Data ◽  
Saxs Data ◽  
X Ray ◽  
X Ray Scattering ◽  
Data Quality Metrics ◽  
Ray Scattering

Small-angle X-ray scattering (SAXS) has grown in popularity in recent times with the advent of bright synchrotron X-ray sources, powerful computational resources and algorithms enabling the calculation of increasingly complex models. However, the lack of standardized data-quality metrics presents difficulties for the growing user community in accurately assessing the quality of experimental SAXS data. Here, a series of metrics to quantitatively describe SAXS data in an objective manner using statistical evaluations are defined. These metrics are applied to identify the effects of radiation damage, concentration dependence and interparticle interactions on SAXS data from a set of 27 previously described targets for which high-resolution structures have been determinedviaX-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. The studies show that these metrics are sufficient to characterize SAXS data quality on a small sample set with statistical rigor and sensitivity similar to or better than manual analysis. The development of data-quality analysis strategies such as these initial efforts is needed to enable the accurate and unbiased assessment of SAXS data quality.

Modelling of small-angle X-ray scattering data using Hermite polynomials

2001 ◽  
Vol 34 (4) ◽  
pp. 510-518 ◽  
Author(s):  
A. K. Swain ◽  
J. K. Parida ◽  
D. K. Bisoyi ◽  
S. Mazumder ◽  
A. K. Mohanty
Keyword(s):  
Experimental Data ◽  
Small Angle ◽  
Hermite Polynomials ◽  
Space Distribution ◽  
Scattering Data ◽  
Ratio Test ◽  
Saxs Data ◽  
X Ray ◽  
X Ray Scattering ◽  
Ray Scattering

A new algorithm, called the term-selection algorithm (TSA), is derived to treat small-angle X-ray scattering (SAXS) data by fitting models to the scattering intensity using weighted Hermite polynomials. This algorithm exploits the orthogonal property of the Hermite polynomials and introduces an error-reduction ratio test to select the correct model terms or to determine which polynomials are to be included in the model and to estimate the associated unknown coefficients. With noa prioriinformation about particle sizes, it is possible to evaluate the real-space distribution function as well as three- and one-dimensional correlation functions directly from the models fitted to raw experimental data. The success of this algorithm depends on the choice of a scale factor and the accuracy of orthogonality of the Hermite polynomials over a finite range of SAXS data. An algorithm to select a weighted orthogonal term is therefore derived to overcome the disadvantages of the TSA. This algorithm combines the properties and advantages of both weighted and orthogonal least-squares algorithms and is numerically more robust for the estimation of the parameters of the Hermite polynomial models. The weighting feature of the algorithm provides an additional degree of freedom to control the effects of noise and the orthogonal feature enables the reorthogonalization of the Hermite polynomials with respect to the weighting matrix. This considerably reduces the error in orthogonality of the Hermite polynomials. The performance of the algorithm has been demonstrated considering both simulated data and experimental data from SAXS measurements of dewaxed cotton fibre at different temperatures.

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