A grid computing-based monte carlo docking simulations approach for computational chiral discrimination

  • Authors:
  • Youngjin Choi;Sung-Ryul Kim;Suntae Hwang;Karpjoo Jeong

  • Affiliations:
  • Department of Microbial Engineering, Konkuk University, Seoul, Korea;Department of Internet and Multimedia & Center for Advanced, e-System Integration Technology, Konkuk University, Seoul, Korea;Department of Computer Science, Kookmin University, Seoul, Korea;Department of Internet and Multimedia & Applied Grid Computing Center, Konkuk University, Seoul, Korea

  • Venue:
  • RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
  • Year:
  • 2005

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Abstract

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 force 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.