Improved Optimization Model And Algorithm In Molecular Docking

High cost and low efficiency are a remarkable character of the drug design, which have become a serious problem in medicine development. Computer-aided drug design plays a important role in the medicine development, which combined with the computer technical, optimization and drug molecular design. Typical optimum designs need to establish an optimization model with the functions and some design constraints and design the effective algorithms for solving the model. By means of optimization design, the efficiency and accuracy of drug molecular design can be improved and the price of preceding stage of the drug design reduced greatly.The research work of the dissertation is to construct a new optimization model for the drug molecular docking and design an improved algorithm, making drug molecular docking accurate and quick.First, a summary of the molecular docking in drug design and the status of optimization (including the improved genetic algorithm, which is important in the dissertation) is introduced. Then two kinds of new optimization model is made, which is called Escore and Kscore separately. Basing on the new model and improved genetic algorithm, two molecular docking programmers EGAsDock and KGAsDock have been developed.A test of reverting the structure of compounding and predicting the binding energy is used to exam the rationality and practicability of EGAsDock and KGAsDock. The results show that two kinds of method have excellent capability in establishing the optimization objective. Especially, the function based on knowledge Kscore will be very useful in the development for DNA/RNA research.