Computational Methods for Predicting Protein-protein Interactions and Binding Sites
Abstract
Proteins are essential to organisms and participate in virtually every process within cells. Quite often, they keep the cells functioning by interacting with other proteins. This process is called protein-protein interaction (PPI). The bonding amino acid residues during the process of protein-protein interactions are called PPI binding sites. Identifying PPIs and PPI binding sites are fundamental problems in system biology.
Experimental methods for solving these two problems are slow and expensive. Therefore, great efforts are being made towards increasing the performance of computational methods.
We present DELPHI, a deep learning based program for PPI site prediction and SPRINT, an algorithmic based program for PPI prediction. Both programs have been compared to the state-of-the-art programs on several datasets. Both DELPHI and SPRINT are more accurate than the competing method. SPRINT is also orders of magnitudes faster while using very little memory.
The dataset and source code for both DELPHI and SPRINT are publicly available at: github.com/lucian-ilie and and www.csd.uwo.ca/~ilie/software.html