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Each and every biological function in living organism occurs due to protein-protein interactions. The diseases are no exception to this. Identifying one or more proteins for a particular disease and then designing a suitable chemical compound (which is known as drug or ligand) to destroy those proteins is a challenging topic of research in computational biology. In earlier methods, drugs were designed using only a few chemical components and were represented as a fixed-length tree. But in reality, a drug contains many chemical groups collectively known as pharmacophore. Moreover, the chemical length of the drug cannot be determined before designing that drug. In the present work, a Particle Swarm Optimization (PSO) based methodology has been proposed to find out a suitable drug for a particular disease so that the drug-target protein interaction energy becomes minimum. In the proposed algorithm, the drug is represented as a variable length tree and essential functional groups are arranged in different positions of that drug. Finally, the structure of the drug is obtained and its docking energy is minimized simultaneously. Also, the orientation of chemical groups in the drug is tested so that it can bind to a particular active site of a target protein and the drug fits well inside the active site of target protein. Here, several inter-molecular forces have been considered for accuracy of the docking energy. Results are demonstrated for three different target proteins both numerically and pictorially. Results show that PSO performs better than the earlier methods.

Determining Stable ligand Orientation Using Particle Swarm Optimization