A database of calculated solution parameters for the recently released AlphaFold predicted protein structures

Recent spectacular advances by AI programs in 3D structure predictions from protein sequences have revolutionized the field in terms of accuracy and speed. The resulting "folding frenzy" has already produced predicted protein structure databases for the entire human and other organisms' proteomes. However, rapidly ascertaining a predicted structure's reliability based on measured properties in solution should be considered. Shape-sensitive hydrodynamic parameters such as the diffusion and sedimentation coefficients (D0t(20,w),s0(20,w)) and the intrinsic viscosity ([η]) can provide a rapid assessment of the overall structure likeliness, and SAXS would yield the structure-related pair-wise distance distribution function p(r) vs. r. Using the extensively validated UltraScan SOlution MOdeler (US-SOMO) suite we have calculated from the AlphaFold structures the corresponding D0t(20,w), s0(20,w), [η], p(r) vs. r, and other parameters. Circular dichroism spectra were also computed. The resulting US-SOMO-AF database should aid in rapidly evaluating the consistency in solution of AlphaFold predicted protein structures.

Optimization of Transmitter-Receiver Pairing of Spaceborne Cluster Flight Netted Radar for Area Coverage and Target Detection

In this paper, we investigate the optimization problem of the transmitter-receiver pairing of spaceborne cluster flight netted radar (SCFNR) for area coverage and target detection. First of all, we propose the novel concept of SCFNR integrated cluster flight spacecraft with netted radar, the mobility model for bistatic radar pair with twin-satellite mode, and formulate the radar-target distance distribution function and radar-target distance product distribution function with geometric probability method. Secondly, by dividing surveillance region into grids, we define the 0-1 grid coverage matrix for bistatic radar and the transmitter-receiver pairing matrix for SCFNR with using radar equation and the radar-target distance distribution function, and we describe the optimal problem of transmitter-receiver pairing of SCFNR for area coverage and target detection by defining K-grid coverage matrix. Thirdly, we propose a new algorithm integrated particle swarm optimization with Hungarian algorithm (PSO-HA) to address the optimal problem, which is actually one-to-one pairing problem. Finally, we validate the effectiveness and reasonability of the proposed algorithm through numerical analysis.

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.

Interpretation of solution scattering data from lipid nanodiscs

The structural information contained in solution scattering data from empty lipid nanodiscs is examined in the context of a multi-component geometric model. X-ray scattering data were collected on nanodiscs of different compositions at scattering vector magnitudes up to 2.0 Å−1. Through the calculation of the partial form factor for each of the nanodisc components before the isotropic average, structural parameters in the model were correlated to the features observed in the X-ray scattering data and to the corresponding distance distribution function. It is shown that, in general, the features at ∼0.3–0.6 Å−1in the scattering data correlate to the bilayer structure. The data also support the argument that the elliptical shape of nanodiscs found in model fitting is physical, rather than an artefact due to the nanodisc size distribution. The lipid chain packing peak at ∼1.5 Å−1is visible in the data and reflects the lipid bilayer phase transition. The shape change in the distance distribution function across the phase transition suggests that the nanodiscs are more circular in the fluid phase. The implication of these findings for model fitting of empty and protein-loaded nanodiscs is discussed.

Analytical solution of the PELDOR inverse problem using the integral Mellin transform

The model-free approach used does not introduce systematic distortions in the computed distance distribution function between two spins and appears to result in noise grouping in the short distance range.

Multi-Gaussian Monte Carlo Analysis of PELDOR Data in the Frequency Domain

Pulsed double electron–electron resonance technique (PELDOR or DEER) is often applied to study conformations and aggregation of spin-labelled macromolecules. Because of the ill-posed nature of the integral equation determining the distance distribution function, a regularization procedure is required to restrict the smoothness of the solution. In this work, we performed PELDOR measurements for new flexible nitroxide biradicals based on trolox, which is the synthetic analogue of

Indirect Fourier transform in the context of statistical inference

Inferring structural information from the intensity of a small-angle scattering (SAS) experiment is an ill-posed inverse problem. Thus, the determination of a solution is in general non-trivial. In this work, the indirect Fourier transform (IFT), which determines the pair distance distribution function from the intensity and hence yields structural information, is discussed within two different statistical inference approaches, namely a frequentist one and a Bayesian one, in order to determine a solution objectively From the frequentist approach the cross-validation method is obtained as a good practical objective function for selecting an IFT solution. Moreover, modern machine learning methods are employed to suppress oscillatory behaviour of the solution, hence extracting only meaningful features of the solution. By comparing the results yielded by the different methods presented here, the reliability of the outcome can be improved and thus the approach should enable more reliable information to be deduced from SAS experiments.

A Thermal Infrared and Visible Images Fusion Based Approach for Multitarget Detection under Complex Environment

Multitarget detection under complex environment is a challenging task, where the measured signal will be submerged by noise. D-S belief theory is an effective approach in dealing with Multitarget detection. However, there are some limitations of the general D-S belief theory under complex environment. For example, the basic belief assignment is difficult to establish, and the subjective factors will influence the update process of evidence. In this paper, a new Multitarget detection approach based on thermal infrared and visible images fusion is proposed. To easily characterize the defected heterogeneous image, a basic belief assignment based on the distance distribution function of heterogeneous characteristics is presented. Furthermore, to improve the discrimination and effectiveness of the Multitarget detection, a concept of comprehensive credibility is introduced into the proposed approach and a new update rule of evidence is designed. Finally, some experiments are carried out and the experimental results show the efficiency and effectiveness of the proposed approach in the Multitarget detection task.

Fault Location for Distribution Networks Based on Node Voltage Equation

Proposed a single end fault location algorithm based on fault distance distribution function to implement fault location for isolated neutral system. Based on bus impedance matrix, establish fault distance distribution function adapted to all kind of asymmetric shorted fault in insulated neutral system. Combine the voltage sag data measured at substation to determine the most possible fault point through data matching and analysis. The method can implement fault location for all kind of asymmetric shorted fault and doesnt need much iterative procedure. Also, it is applicable to complicated systems with multi-branch and is quite robust to load variations. Simulation results for a 10Kv typical distribution network verify the validity of the method.