17 research outputs found
Rapid automated superposition of shapes and macromolecular models using spherical harmonics
Automating Stimulation Frequency Selection for SSVEP-Based Brain-Computer Interfaces
Brain–computer interfaces (BCIs) based on steady-state visually evoked potentials (SSVEPs) are inexpensive and do not require user training. However, the highly personalized reaction to visual stimulation is an obstacle to the wider application of this technique, as it can be ineffective, tiring, or even harmful at certain frequencies. In our experimental study, we proposed a new approach to the selection of optimal frequencies of photostimulation. By using a custom photostimulation device, we covered a frequency range from 5 to 25 Hz with 1 Hz increments, recording the subjects’ brainwave activity (EEG) and analyzing the signal-to-noise ratio (SNR) changes at the corresponding frequencies. The proposed set of SNR-based coefficients and the discomfort index, determined by the ratio of theta and beta rhythms in the EEG signal, enables the automation of obtaining the recommended stimulation frequencies for use in SSVEP-based BCIs
Novel Genes Involved in Hypertrophic Cardiomyopathy: Data of Transcriptome and Methylome Profiling
Hypertrophic cardiomyopathy (HCM) is the most common inherited heart disease; its pathogenesis is still being intensively studied to explain the reasons for the significant genetic and phenotypic heterogeneity of the disease. To search for new genes involved in HCM development, we analyzed gene expression profiles coupled with DNA methylation profiles in the hypertrophied myocardia of HCM patients. The transcriptome analysis identified significant differences in the levels of 193 genes, most of which were underexpressed in HCM. The methylome analysis revealed 1755 nominally significant differentially methylated positions (DMPs), mostly hypomethylated in HCM. Based on gene ontology enrichment analysis, the majority of biological processes, overrepresented by both differentially expressed genes (DEGs) and DMP-containing genes, are involved in the regulation of locomotion and muscle structure development. The intersection of 193 DEGs and 978 DMP-containing genes pinpointed eight common genes, the expressions of which correlated with the methylation levels of the neighboring DMPs. Half of these genes (AUTS2, BRSK2, PRRT1, and SLC17A7), regulated by the mechanism of DNA methylation, were underexpressed in HCM and were involved in neurogenesis and synapse functioning. Our data, suggesting the involvement of innervation-associated genes in HCM, provide additional insights into disease pathogenesis and expand the field of further research
Global Rigid Body Modeling of Macromolecular Complexes against Small-Angle Scattering Data
New methods to automatically build models of macromolecular complexes from high-resolution structures or homology models of their subunits or domains against x-ray or neutron small-angle scattering data are presented. Depending on the complexity of the object, different approaches are employed for the global search of the optimum configuration of subunits fitting the experimental data. An exhaustive grid search is used for hetero- and homodimeric particles and for symmetric oligomers formed by identical subunits. For the assemblies or multidomain proteins containing more then one subunit/domain per asymmetric unit, heuristic algorithms based on simulated annealing are used. Fast computational algorithms based on spherical harmonics representation of scattering amplitudes are employed. The methods allow one to construct interconnected models without steric clashes, to account for the particle symmetry and to incorporate information from other methods, on distances between specific residues or nucleotides. For multidomain proteins, addition of missing linkers between the domains is possible. Simultaneous fitting of multiple scattering patterns from subcomplexes or deletion mutants is incorporated. The efficiency of the methods is illustrated by their application to complexes of different types in several simulated and practical examples. Limitations and possible ambiguity of rigid body modeling are discussed and simplified docking criteria are provided to rank multiple models. The methods described are implemented in publicly available computer programs running on major hardware platforms
X-ray and neutron small-angle scattering analysis of the complex formed by the Met receptor and the Listeria monocytogenes invasion protein InlB
The Listeria monocytogenes surface protein InlB binds to the extracellular domain of the human receptor tyrosine kinase Met, the product of the c-met proto-oncogene. InlB binding activates the Met receptor, leading to uptake of Listeria into normally nonphagocytic host cells. The N-terminal half of InlB (InlB(321)) is sufficient for Met binding and activation. The complex between this Met-binding domain of InlB and various constructs of the Met ectodomain was characterized by size exclusion chromatography and dynamic light scattering, and structural models were built using small-angle X-ray scattering and small-angle neutron scattering. Although most receptor tyrosine kinase ligands induce receptor dimerization, InlB(321) consistently binds the Met ectodomain with a 1:1 stoichiometry. A construct comprising the Sema and PSI domains of Met, although sufficient to bind the physiological Met ligand hepatocyte growth factor/scatter factor, does not form a complex with InlB(321) in solution, highlighting the importance of Met Ig domains for InlB binding. Small-angle X-ray scattering and small-angle neutron scattering measurements of ligand and receptor, both free and in complex, reveal an elongated shape for the receptor. The four Ig domains form a bent, rather than a fully extended, conformation, and InlB(321) binds to Sema and the first Ig domain of Met, in agreement with the recent crystal structure of a smaller Met fragment in complex with InlB(321). These results call into question whether receptor dimerization is the basic underlying event in InlB(321)-mediated Met activation and demonstrate differences in the mechanisms by which the physiological ligand hepatocyte growth factor/scatter factor and InlB(321) bind and activate the Met receptor