Abstract P-5: Neural Network Approaches to Classify 3D Protein Structures from the Data of X-ray Laser Radiation Diffraction from Single Particles

Background: Protein structure determination using X-ray free-electron laser (XFEL) includes analysis and merging a large number of snapshot diffraction patterns. Convolutional neural networks are widely used to solve numerous computer vision problems, e.g. image classification, and can be used for diffraction pattern analysis. But the task of protein structure determination with the use of CNNs only is not yet solved. Methods: We simulated the diffraction patterns using the Condor software library and obtained more than 1000 diffraction patterns for each structure with simulation parameters resembling real ones. To classify diffraction patterns, we tried two approaches, which are widely known in the area of image classification: a classic VGG network and residual networks. Results: 1. Recognition of a protein class (GPCRs vs globins). Globins and GPCR-like proteins are typical α-helical proteins. Each of these protein families has a large number of representatives (including those with known structure) but we used only 8 structures from every family. 12,000 of diffraction patterns were used for training and 4,000 patterns for testing. Results indicate that all considered networks are able to recognize the protein family type with high accuracy. 2. Recognition of the number of protein molecules in the liposome. We considered the usage of lyposomes as carriers of membrane or globular proteins for sample delivery in XFEL experiments in order to improve the X-ray beam hit rate. Three sets of diffractograms for liposomes of various radius were calculated, including diffractograms for empty liposomes, liposomes loaded with 5 bacteriorhodopsin molecules, and liposomes loaded with 10 bacteriorhodopsin molecules. The training set consisted of 23625 diffraction patterns, and test set of 7875 patterns. We found that all networks used in our study were able to identify the number of protein molecules in liposomes independent of the liposome radius. Our findings make this approach rather promising for the usage of liposomes as protein carriers in XFEL experiments. Conclusion: Thus, the performed numerical experiments show that the use of neural network algorithms for the recognition of diffraction images from single macromolecular particles makes it possible to determine changes in the structure at the angstrom scale

Computer simulations of self-assembling nanofibers from thiophene-peptide oligomers

Polythiophenes are conductive polymers with outstanding semiconducting, optical, electroluminescent and processing properties making them a promising compound class for applications in organic electronics, sensor design, etc. The ability to organize molecules into various functional structures at micro and nano scale in a controlled fashion is now seen as an important challenge which will contribute to the ongoing technological revolution in the field of nanotechnology. A perspective approach towards the design of such structures is the chemical conjugation of synthetic polymers with specific biopolymers which are known to self-assemble into well ordered supramolecular aggregates. Several new hybrid compounds have been recently synthesized containing the oligothiophene moiety conjugated with a beta-sheet forming peptide, which are known to self-assemble into amyloid-like fibrillar structures similar to those featured in many human diseases (Alzheimer, type II diabetes, etc.). These compounds were indeed shown to self-assemble into fibrillar aggregates (molecular nanowires) in organic solvent. However, the structure of the aggregates as well as the rational understanding of the self-assembly principles and their properties remained elusive. In this thesis we aimed at applying an arsenal of theoretical approaches, including molecular mechanics, molecular dynamics, crystalline packing prediction, dissipative particle dynamics, quantum chemistry calculations, etc. to deduce the possible atomistic models for the arrangement of the molecules in the observed fibrils, to study their morphological, conformational and conducting properties, as well as to develop a methodology for computer simulations of these complex systems

Nucleosome adaptability conferred by sequence and structural variations in histone H2A–H2B dimers

Nucleosome variability is essential for their functions in compacting the chromatin structure and regulation of transcription, replication and cell reprogramming. The DNA molecule in nucleosomes is wrapped around an octamer composed of four types of core histones (H3, H4, H2A, H2B). Nucleosomes represent dynamic entities and may change their conformation, stability and binding properties by employing different sets of histone variants or by becoming post-translationally modified. There are many variants of histones H2A and H2B. Specific H2A and H2B variants may preferentially associate with each other resulting in different combinations of variants and leading to the increased combinatorial complexity of nucleosomes. In addition, the H2A–H2B dimer can be recognized and substituted by chaperones/remodelers as a distinct unit, can assemble independently and is stable during nucleosome unwinding. In this review we discuss how sequence and structural variations in H2A–H2B dimers may provide necessary complexity and confer the nucleosome functional variability

H2A-H2B Histone Dimer Plasticity and Its Functional Implications

The protein core of the nucleosome is composed of an H3-H4 histone tetramer and two H2A-H2B histone dimers. The tetramer organizes the central 60 DNA bp, while H2A-H2B dimers lock the flanking DNA segments. Being positioned at the sides of the nucleosome, H2A-H2B dimers stabilize the overall structure of the nucleosome and modulate its dynamics, such as DNA unwrapping, sliding, etc. Such modulation at the epigenetic level is achieved through post-translational modifications and the incorporation of histone variants. However, the detailed connection between the sequence of H2A-H2B histones and their structure, dynamics and implications for nucleosome functioning remains elusive. In this work, we present a detailed study of H2A-H2B dimer dynamics in the free form and in the context of nucleosomes via atomistic molecular dynamics simulations (based on X. laevis histones). We supplement simulation results by comparative analysis of information in the structural databases. Particularly, we describe a major dynamical mode corresponding to the bending movement of the longest H2A and H2B α-helices. This overall bending dynamics of the H2A-H2B dimer were found to be modulated by its interactions with DNA, H3-H4 tetramer, the presence of DNA twist-defects with nucleosomal DNA and the amino acid sequence of histones. Taken together, our results shed new light on the dynamical mechanisms of nucleosome functioning, such as nucleosome sliding, DNA-unwrapping and their epigenetic modulation

Voltage-gated ion channel modulation by lipids: Insights from molecular dynamics simulations

AbstractCells commonly use lipids to modulate the function of ion channels. The lipid content influences the amplitude of the ionic current and changes the probability of voltage-gated ion channels being in the active or in the resting states. Experimental findings inferred from a variety of techniques and molecular dynamics studies have revealed a direct interaction between the lipid headgroups and the ion channel residues, suggesting an influence on the ion channel function. On the other hand the alteration of the lipids may in principle modify the overall electrostatic environment of the channel, and hence the transmembrane potential, leading to an indirect modulation, i.e. a global effect. Here we have investigated the structural and dynamical properties of the voltage-gated potassium channel Kv1.2 embedded in bilayers with modified upper or lower leaflet compositions corresponding to realistic biological scenarios: the first relates to the effects of sphingomyelinase, an enzyme that modifies the composition of lipids of the outer membrane leaflets, and the second to the effect of the presence of a small fraction of PIP2, a highly negatively charged lipid known to modulate voltage-gated channel function. Our molecular dynamics simulations do not enable to exclude the global effect mechanism in the former case. For the latter, however, it is shown that local interactions between the ion channel and the lipid headgroups are key-elements of the modulation