Publications by authors named "E D Grigorashvili"

Deep learning is a class of machine learning techniques capable of creating internal representation of data without explicit preprogramming. Hence, in addition to practical applications, it is of interest to analyze what features of biological data may be learned by such models. Here, we describe PredPair, a deep learning neural network trained to predict base pairs in RNA structure from sequence alone, without any incorporated prior knowledge, such as the stacking energies or possible spatial structures.

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As has been recently shown, the toxicity of protein aggregates is determined by their structure. Therefore, special attention has been focused on the search for factors that specify the structural features of formed amyloid fibrils. The effect of amino acid substitutions in apomyoglobin on the structural characteristics of its amyloid aggregates has been analyzed.

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It has been demonstrated using Aβ40 and Aβ42 recombinant and synthetic peptides that their fibrils are formed of complete oligomer ring structures. Such ring structures have a diameter of about 8-9 nm, an oligomer height of about 2- 4 nm, and an internal diameter of the ring of about 3-4 nm. Oligomers associate in a fibril in such a way that they interact with each other, overlapping slightly.

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We performed a comparative study of the process of amyloid formation by short homologous peptides with a substitution of aspartate for glutamate in position 2 - VDSWNVLVAG (AspNB) and VESWNVLVAG (GluNB) - with unblocked termini. Peptide AspNB (residues 166-175) corresponded to the predicted amyloidogenic region of the protein glucantransferase Bgl2 from the Saccharomyces cerevisiae cell wall. The process of amyloid formation was monitored by fluorescence spectroscopy (FS), electron microscopy (EM), tandem mass spectrometry (TMS), and X-ray diffraction (XD) methods.

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The studies of amyloid structures and the process of their formation are important problems of biophysics. One of the aspects of such studies is to determine the amyloidogenic regions of a protein chain that form the core of an amyloid fibril. We have theoretically predicted the amyloidogenic regions of the Aβ(1-40) peptide capable of forming an amyloid structure.

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