首页> 外文会议>International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing(RSFDGrC 2005) pt.2; 20050831-0903; Regina(CA) >A Grid Computing-Based Monte Carlo Docking Simulations Approach for Computational Chiral Discrimination
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A Grid Computing-Based Monte Carlo Docking Simulations Approach for Computational Chiral Discrimination

机译:基于网格计算的蒙特卡罗对接仿真方法用于计算手性识别

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A validity of Grid computing with Monte Carlo (MC) docking simulations was examined in order to execute prediction and data handling for the computational chiral discrimination. Docking simulations were performed with various computational parameters for the chiral discrimination of a series of 17 enantiomers by β-cyclodextrin (β-CD) or by 6-amino-6-deoxy-β-cyclodextrin (am-β-CD). Rigid-body MC docking simulations gave more accurate predictions than flexible docking simulations. The accuracy was also affected by both the simulation temperature and the kind of foree field. The prediction rate of chiral preference was improved by as much as 76.7% when rigid-body MC docking simulations were performed at low temperatures (100 K) with a sugar22 parameter set in the CHARMM force field. Our approach for Grid-based MC docking simulations suggested the conformational rigidity of both the host and guest molecule.
机译:为了执行计算手性识别的预测和数据处理,检查了具有蒙特卡洛(MC)对接模拟的网格计算的有效性。用各种计算参数进行对接模拟,以通过β-环糊精(β-CD)或通过6-氨基-6-脱氧-β-环糊精(am-β-CD)手性区分一系列17种对映异构体。刚体MC对接仿真比灵活对接仿真提供了更准确的预测。模拟温度和前场类型也影响精度。当在低温(100 K)下使用CHARMM力场中设置的sugar22参数进行刚体MC对接模拟时,手性偏好的预测率提高了76.7%。我们基于网格的MC对接模拟的方法表明了主体分子和客体分子的构象刚性。

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