The Investigation And Implementation Of Molecular Docking Based On Swarm Intelligence

Molecular docking is a powerful approach in computer-aided drug discovery and drug design. The computer mode identification and optimization technique are used to search molecule in three dimensional small molecular database, the special molecule matches with the active site of the specially designed target relating disease in geometry, physics and chemical characteristics. In this way, the computer screening (virtual screening) can be used to drug design. From the view of thermodynamics, native complex is the structure with the lowest binding free energy. Therefore, the aim of docking is to find the conformation with the lowest binding free energy. So there are two important factors in the docking problem. One is an efficient search algorithm, which can explore the relevant conformational space, and the other is a good scoring function, which should reflect the affinity of the two proteins and guide the process of search.The major concept of this paper will focus on optimization algorithm. After analysed the swarm intelligence algorithms, we developed FIPSDock, ABCDock and AFSADock based on the classical variants of PSO, ABC and AFSA and the classical molecular docking platform AutoDock. Comprehensive experiments were conducted on all of those optimization methods. The results demonstrated that FIPSDock, ABCDock and AFSADock suppress LGA in term of convergence speed, stability and accuracy. This investigation also compared them with the other state-of-the-art docking methods, namely GOLD, DOCK, FlexX. FIPSDock, ABCDock and AFSADock suppress all the four docking methods in term of accuracy.