In this work, we further developed a new approach for modeling the processes of the self-assembly of complex molecular nanostructures using molecular dynamics methods; in particular, using a molecular dynamics manipulator. Previously, this approach was considered using the example of the self-assembly of a phenylalanine helical nanotube. Now, a new application of the algorithm has been developed for implementing a similar molecular dynamic self-assembly into helical structures of peptide nanotubes (PNTs) based on other peptide molecules-namely diphenylalanine (FF) molecules of different chirality L-FF and D-FF. In this work, helical nanotubes were assembled from linear sequences of FF molecules with these initially different chiralities. The chirality of the obtained nanotubes was calculated by various methods, including calculation by dipole moments. In addition, a statistical analysis of the results obtained was performed. A comparative analysis of the structures of nanotubes was also performed using the method of visual differential analysis. It was found that FF PNTs obtained by the MD self-assembly method form helical nanotubes of different chirality. The regimes that form nanotubes of right chirality D from initial L-FF dipeptides and nanotubes of left chirality L from D-FF dipeptides are revealed. This corresponds to the law of changing the sign of the chirality of molecular helical structures as the level of their hierarchical organization becomes more complicated.
Keywords: chirality; controlled molecular dynamics; diphenylalanine; dipole moment; molecular dynamics method; nanotubes; self-assembly of nanostructures; visual differential analysis.