Artificial neural networks for solution scattering data analysis.

Small-angle X-ray scattering (SAXS) experiments are widely used for the characterization of biological macromolecules in solution. SAXS patterns contain information on the size and shape of dissolved particles in nanometer resolution. Here we propose a method for primary SAXS data analysis based on the application of artificial neural networks (NNs). Trained on synthetic SAXS data, the feedforward NNs are able to reliably predict molecular weight and maximum intraparticle distance (Dmax) directly from the experimental data. The method is applicable to data from monodisperse solutions of folded proteins, intrinsically disordered proteins, and nucleic acids. Extensive tests on synthetic SAXS data generated in various angular ranges with varying levels of noise demonstrated a higher accuracy and better robustness of the NN approach compared to the existing methods.

The role of SAXS and molecular simulations in 3D structure elucidation of a DNA aptamer against lung cancer.

Aptamers are short, single-stranded DNA or RNA oligonucleotide molecules that function as synthetic analogs of antibodies and bind to a target molecule with high specificity. Aptamer affinity entirely depends on its tertiary structure and charge distribution. Therefore, length and structure optimization are essential for increasing aptamer specificity and affinity. Here, we present a general optimization procedure for finding the most populated atomistic structures of DNA aptamers. Based on the existed aptamer LC-18 for lung adenocarcinoma, a new truncated LC-18 (LC-18t) aptamer LC-18t was developed. A three-dimensional (3D) shape of LC-18t was reported based on small-angle X-ray scattering (SAXS) experiments and molecular modeling by fragment molecular orbital or molecular dynamic methods. Molecular simulations revealed an ensemble of possible aptamer conformations in solution that were in close agreement with measured SAXS data. The aptamer LC-18t had stronger binding to cancerous cells in lung tumor tissues and shared the binding site with the original larger aptamer. The suggested approach reveals 3D shapes of aptamers and helps in designing better affinity probes.

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

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.

An automated data processing and analysis pipeline for transmembrane proteins in detergent solutions.

The application of small angle X-ray scattering (SAXS) to the structural characterization of transmembrane proteins (MPs) in detergent solutions has become a routine procedure at synchrotron BioSAXS beamlines around the world. SAXS provides overall parameters and low resolution shapes of solubilized MPs, but is also meaningfully employed in hybrid modeling procedures that combine scattering data with information provided by high-resolution techniques (eg. macromolecular crystallography, nuclear magnetic resonance and cryo-electron microscopy). Structural modeling of MPs from SAXS data is non-trivial, and the necessary computational procedures require further formalization and facilitation. We propose an automated pipeline integrated with the laboratory-information management system ISPyB, aimed at preliminary SAXS analysis and the first-step reconstruction of MPs in detergent solutions, in order to streamline high-throughput studies, especially at synchrotron beamlines. The pipeline queries an ISPyB database for available a priori information via dedicated services, estimates model-free SAXS parameters and generates preliminary models utilizing either ab initio, high-resolution-based, or mixed/hybrid methods. The results of the automated analysis can be inspected online using the standard ISPyB interface and the estimated modeling parameters may be utilized for further in-depth modeling beyond the pipeline. Examples of the pipeline results for the modelling of the tetrameric alpha-helical membrane channel Aquaporin0 and mechanosensitive channel T2, solubilized by n-Dodecyl ß-D-maltoside are presented. We demonstrate how increasing the amount of a priori information improves model resolution and enables deeper insights into the molecular structure of protein-detergent complexes.

SASBDB: Towards an automatically curated and validated repository for biological scattering data.

Small-angle scattering (SAS) of X-rays and neutrons is a fundamental tool to study the nanostructural properties, and in particular, biological macromolecules in solution. In structural biology, SAS recently transformed from a specialization into a general technique leading to a dramatic increase in the number of publications reporting structural models. The growing amount of data recorded and published has led to an urgent need for a global SAS repository that includes both primary data and models. In response to this, a small-angle scattering biological data bank (SASBDB) was designed in 2014 and is available for public access at www.sasbdb.org. SASBDB is a comprehensive, free and searchable repository of SAS experimental data and models deposited together with the relevant experimental conditions, sample details and instrument characteristics. SASBDB is rapidly growing, and presently has over 1,000 entries containing more than 1,600 models. We describe here the overall organization and procedures of SASBDB paying most attention to user-relevant information during submission. Perspectives of further developments, in particular, with OneDep system of the Protein Data Bank, and also widening of SASBDB including new types of data/models are discussed.