Self-adaptive differential evolution algorithm incorporating local search for protein-ligand docking
- Self-adaptive differential evolution algorithm incorporating local search for protein-ligand docking
- 정환원; 조승주; 이광렬; 이규환
- Differential Evolution; Self-adaptive; Protein-Ligand Docking; Local Search
- Issue Date
- IC-MSQUARE 2012
- Di erential Evolution (DE) algorithm is powerful in optimization problems over
several real parameters. DE depends on strategies to generate new trial solutions and the
associated parameter values for searching performance. In self-adaptive DE, the automatic
learning about previous evolution was used to determine the best mutation strategy and its
parameter settings. By combining the self-adaptive DE and Hooke Jeeves local search, we
developed a new docking method named SADock (Strategy Adaptation Dock) with the help
of AutoDock4 scoring function. As the accuracy and performance of SADock was evaluated
in self-docking using the Astex diverse set, the introduced SADock showed better success ratio
(89%) than the success ratio (60%) of the Lamarckian genetic algorithm (LGA) of AutoDock4.
The self-adapting scheme enabled our new docking method to converge fast and to be robust
through the various docking problems.
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- KIST Publication > Conference Paper
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