An improved adaptive genetic algorithm for protein–ligand docking
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A new optimization model of molecular docking is proposed, and a fast flexible docking method based on an improved adaptive genetic algorithm is developed in this paper. The algorithm takes some advanced techniques, such as multi-population genetic strategy, entropy-based searching technique with self-adaptation and the quasi-exact penalty. A new iteration scheme in conjunction with above techniques is employed to speed up the optimization process and to ensure very rapid and steady convergence. The docking accuracy and efficiency of the method are evaluated by docking results from GOLD test data set, which contains 134 protein–ligand complexes. In over 66.2% of the complexes, the docked pose was within 2.0 Å root-mean-square deviation (RMSD) of the X-ray structure. Docking time is approximately in proportion to the number of the rotatable bonds of ligands.
KeywordsGenetic algorithms Information entropy Molecular docking Optimization design Penalty function Self-adaptation
The authors gratefully acknowledge financial support for this work from the National Natural Science Foundation (No. 10772042), the Subsidized by the Special Funds for Major State Basic Research Project (No. 2004CB518901) and High Science and Technology Project (No. 2006AA01A124) of China.
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