Histones play a key role in chromatin organization and gene regulation by modulating nucleosome stability and DNA accessibility. Different histone variants can alter the packing density of DNA and affect cell function. This study demonstrates the successful application of the developed ProBAN neural network to predict the affinity of protein-protein interactions, which can be used to assess the effect of various histone variants on the stability of nucleosomes. It has been shown that the incorporation of histone variants into the nucleosome can stabilize or destabilize the structure of the histone octamer through altered patterns of intermolecular interactions. In particular, replacement histone variants H2A.Z, TSH2A.1-TSH2B.1 (in the form of a dimer) and H3.3 form more stable structures inside the nucleosome than canonical histones, while other variants such as TSH2A.1, TSH2B.1 (separately) and H3.6, demonstrated less stable interactions. The observed differences may explain how cells regulate genes in specialized tissues or during development. These results demonstrate the effect of histone sequence variations on the stability of nucleosomes, which is important for the regulation of transcription and epigenetic mechanisms. The ProBAN algorithm has demonstrated high prediction accuracy, representing a valuable tool for further studying the effect of histone variants on chromatin functioning and disease development.
E. A. Bogdanova (Wed,) studied this question.