Bulletin of the Korean Chemical Society

Korean Chemical Society (대한화학회)
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QM and Pharmacophore based 3D-QSAR of MK886 Analogues against mPGES-1

  • Pasha, F.A. (Computational Science Center, Future Fusion Technology Division, Korea Institute of Science and Technology) ;
  • Muddassar, M. (Computational Science Center, Future Fusion Technology Division, Korea Institute of Science and Technology) ;
  • Jung, Hwan-Won (Computational Science Center, Future Fusion Technology Division, Korea Institute of Science and Technology) ;
  • Yang, Beom-Seok (Computational Science Center, Future Fusion Technology Division, Korea Institute of Science and Technology) ;
  • Lee, Cheol-Ju (Computational Science Center, Future Fusion Technology Division, Korea Institute of Science and Technology) ;
  • Oh, Jung-Soo (Computational Science Center, Future Fusion Technology Division, Korea Institute of Science and Technology) ;
  • Cho, Seung-Joo (Computational Science Center, Future Fusion Technology Division, Korea Institute of Science and Technology) ;
  • Cho, Hoon (College of Engineering, Chosun University)
  • Published : 2008.03.20
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Abstract

Microsomal prostaglandin E2 synthase (mPGES-1) is a potent target for pain and inflammation. Various QSAR (quantitative structure activity relationship) analyses used to understand the factors affecting inhibitory potency for a series of MK886 analogues. We derived four QSAR models utilizing various quantum mechanical (QM) descriptors. These QM models indicate that steric, electrostatic and hydrophobic interaction can be important factors. Common pharmacophore hypotheses (CPHs) also have studied. The QSAR model derived by best-fitted CPHs considering hydrophobic, negative group and ring effect gave a reasonable result (q2 = 0.77, r2 = 0.97 and Rtestset = 0.90). The pharmacophore-derived molecular alignment subsequently used for 3D-QSAR. The CoMFA (Comparative Molecular Field Analysis) and CoMSIA (Comparative Molecular Similarity Indices Analysis) techniques employed on same series of mPGES-1 inhibitors which gives a statistically reasonable result (CoMFA; q2 = 0.90, r2 = 0.99. CoMSIA; q2 = 0.93, r2 = 1.00). All modeling results (QM-based QSAR, pharmacophore modeling and 3D-QSAR) imply steric, electrostatic and hydrophobic contribution to the inhibitory activity. CoMFA and CoMSIA models suggest the introduction of bulky group around ring B may enhance the inhibitory activity.

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References

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