Predicting Protein-Protein Recognition Using Feature Vector
Proteins play an important role in the function of organism. The protein-protein interaction brings the interaction of cells and executes functions of physiology. A protein complex is either permanent or transient. Proteins recognize each other by forming transient complexes. In order to predict protein-protein recognition, we study the residue distribution on the binding sites of the two contacting proteins in a complex. Calpha atoms of the amino acids on the binding site are projected from 3D to 2D plane. We use the distribution of polarity and electricity of residues on the 2D plane to predict protein recognition with neural network model. The prediction accuracy reaches 72% in our experiment.