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Protein can be represented by amino acid interaction network. This network is a graph whose vertices are the proteins amino acids and whose edges are the interactions between them. This interaction network is the first step of proteins three-dimensional structure prediction. In this paper we present a multi-objective evolutionary algorithm for interaction prediction and ant colony probabilistic optimization algorithm is used to confirm the interaction.

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Protein can be represented by amino acid interaction network. This network is a graph whose vertices are the proteins amino acids and whose edges are the interactions between them. In this paper we have formalized amino acid interaction network prediction as a multi-objective evolutionary optimization problem. This formalism is biologically plausible because interactions among amino acids do not depend only on a single factor like atomic distance but also other factors like torsion angle, hydrophobicity and hydrophilicity etc. This problem is then solved and implemented using multi-objective genetic algorithm and subsequently optimized using ant colony optimization technique. The result shows that our algorithm performs better than recent amino acid interaction network prediction algorithms that are based on single factor.