Evolutionary approach for designing protein-protein interaction network using artificial bee colony optimization

In the new paradigm for studying biological phenomena represented by System Biology, cellular components are not considered in isolation but as forming complex networks of relationships. Protein-Protein Interaction (PPI) networks are among the first objects studied from this new point of view. The paper addresses an interesting approach to protein-protein interaction problem using Artificial Bee Colony (ABC) optimization algorithm. In this work, PPI is formulated as an optimization problem. The binding energy and mismatch in phylogenetic profiles of two bound proteins are used as a scoring function for the solutions. Results are demonstrated for three different networks both numerically and pictorially. Experimental results reveal that the proposed method outperforms Differential Evolution (DE) based PPI network design method considering the intra- and inter-molecular energies of the evolved molecules and the phylogenetic profiles of the proteins in the network.