location: Current position: Home >> Scientific Research >> Paper Publications

PARTICLE SWARM OPTIMIZATION ON FLEXIBLE DOCKING

Hits:

Indexed by:期刊论文

Date of Publication:2012-09-01

Journal:INTERNATIONAL JOURNAL OF BIOMATHEMATICS

Included Journals:SCIE、Scopus

Volume:5

Issue:5

ISSN No.:1793-5245

Key Words:AutoDock; particle swarm optimization; molecular docking

Abstract:Molecular docking is an important tool in screening large libraries of compounds to determine the interactions between potential drugs and the target proteins. The molecular docking problem is how to locate a good conformation to dock a ligand to the large molecule. It can be formulated as a parameter optimization problem consisting of a scoring function and a global optimization method. Many docking methods have been developed with primarily these two parts varying. In this paper, a variety of particle swarm optimization (PSO) variants were introduced to cooperate with the semiempirical free energy force field in AutoDock 4.05. The search ability and the docking accuracy of these methods were evaluated by multiple redocking experiments. The results demonstrate that PSOs were more suitable than Lamarckian genetic algorithm (LGA). Among all of the PSO variants, FIPS takes precedence over others. Compared with the four state-of-art docking methods-GOLD, DOCK, FlexX and AutoDock with LGA, AutoDock cooperated with FIPS is more accurate. Thus, FIPS is an efficient PSO variant which has promising prospects that can be expected in the application to virtual screening.

Pre One:基于角色划分的动态社区挖掘算法研究

Next One:关于高水平本科生培养的一点思考