Research On Protein-Protein Interactions Based On Primary Structure

Proteins are probably the most important players in a living cell, a lot of functions of cell have been accomplished by protein interactions. There are stranger relationships between function various and protein-protein interactions, it has two mainly form, including"physical"interactions and function interactions. In general, interaction proteins participate in the same metabolic pathway, and executive same functions, in other words, interaction protein is function interactions.Proteomics is the systematic study of the structure, interactions and functions of protein. It is obviously that protein interaction is the most hot spot in proteomics. The experimental techniques for finding protein-protein interactions have several limitations which stimulated the research in computational way of predicting the interactions. It mainly includes genome, evolution information and based on primary structure of protein. But some of them have many limitations, for instance, the method of genome needs full genome information. However, the approach of protein primary structure, only requires the primary structure of protein, it has no limitations for sequence length and has great application.In this paper, we employ primary structure of protein to predict protein-protein interactions. The statistical method is used to generate sequence features, which are then normalized for satisfying experiments. Few features are calculated for each protein. It involves hydrophobility, molecular weight, polarity and average area buried. And BP neural network,SVM are used to classify two kinds of protein. We used the Scerevisiae yeast dataset to verify the predictive ability of our method, which including 4837 of interaction protein pairs and 9674 of non-interaction protein pairs. Achieving above 87% accuracy rates using 10-fold cross-validation based on BP neural network, and above 64% accuracy rates using SVM.In additional, the experiments manifest that our methods have a good ability to identify and predict interaction protein pairs.