SPRINGS: Prediction of Protein-Protein Interaction Sites Using Artificial Neural Networks

Proteins are key players in biological systems orchestrating various mechanisms of life sustenance and growth. They perform such vital functions by concerting interactions with each other forming a network of interplaying agents in regulating as well as facilitating various metabolic functions within and outside of the organisms [1]. Thus, knowledge of protein-protein interactions can provide us with insights into the innate metabolic machinery of living organisms. Further, with newer annotations of protein sequences and structures, mapping protein interaction network has become a coveted aspect of advancing towards its potential applications in proteomics and related fields also [2]. Since protein-protein interaction information allows the function of a protein to be defined by its position in a complex web of interacting proteins, access to such information is believed to have ample role in boosting biological research and drug discovery [3]. These insights can be utilized to develop novel agents for intervening and manipulating the flow of biological information in case of disorders and irregularities [4,5].