Predict Protein-Protein Interaction using Heuristic Approaches

Proteins interact with each other for a common purpose such as cell formation. They come in contact with each other following the biochemical properties. The understanding of protein-protein interactions in metabolic networks is an important aspect of molecular biology and biochemistry. The proposed prediction system uses protein sequence data to learn the interactions. Based on sequence data, the information about the accessible interface and the type of forces that form this interface can be extracted. This solution to the problem offers a great help in the field of drug design. The paper presents an approach which takes into consideration the structure of proteins and also the types of forces that mediate the interactions among the proteins. The heuristic technique has been applied to find the interface surface, which is active in a protein during interaction. Since finding an interface that takes part in the interaction is practically complicated, a similar interface can always be found. The heuristic technique is applied in such a way that considers the protein sequence data minutely in interaction prediction. The system modeled in this paper gives a high value of sensitivity (88%) on the dataset collected from DIP (database of interacting proteins)