Modeling of the three-dimensional structure of luffin-alpha and its simulated reaction with the substrate oligoribonucleotide GAGA.

A fundamental problem in biochemistry and molecular biology is understanding the spatial structure of macromolecules and then analyzing their functions. In this study, the three-dimensional structure of a ribosome-inactivating protein luffin-alpha was predicted using a neural network method and molecular dynamics simulation. A feedforward neural network with the backpropagation learning algorithm were trained on model class of homologous proteins including trichosanthin and alpha-momorcharin. The distance constraints for the C alpha atoms in the protein backbone were utilized to generate a folded crude conformation of luffin-alpha by model building and the steepest descent minimization approach. The crude conformation was refined by molecular dynamics techniques and a simulated annealing procedure. The interaction between luffin-alpha and its analogous substrate GAGA was also simulated to understand its action mechanism.