Targeted Drug Delivery / Smart Drug Delivery / Drug Targeting
Mohammad Koohimoghadam; Adel Torkamaan Rahmani
Volume 5, Issue 4 , June 2011, , Pages 333-351
Abstract
Discovery of new drugs and study of their side effects has been an important research field in recent years. Because of direct effect of the pharmaceutical products on human health usually the drug design projects are challenging and technically demanding. The incorporation of computer simulations into ...
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Discovery of new drugs and study of their side effects has been an important research field in recent years. Because of direct effect of the pharmaceutical products on human health usually the drug design projects are challenging and technically demanding. The incorporation of computer simulations into drug design projects is one of the best ways to optimize drugs' potency. In this approach, researchers try to find the best interaction between protein structure and drug in a virtual environment; this procedure is called "molecular docking". The molecular docking problem can be considered as a search problem. The search space in this problem is defined with all possible protein-ligand interactions and the best interaction is the solution of problem. In this paper, a new approach for finding the best interaction is proposed. The proposed method is based on opposition based differential evolution algorithm. Also the proposed method is enhanced by a local search algorithm and a pseudo-elitism operator. Like other metaheuristic algorithms, our method uses a population of possible solution and AutoDock scoring function is used to evaluate each vector in the population. Six different protein-ligand complexes are used to verify the efficiency of the proposed algorithm. The experimental results show that the proposed algorithm is more robust and reliable than other algorithms such as simulated annealing and Lamarckian genetic algorithm.
