Journal of Computer-Aided Molecular Design

, Volume 20, Issue 9, pp 549–566

QSAR analyses on avian influenza virus neuraminidase inhibitors using CoMFA, CoMSIA, and HQSAR

  • Mingyue Zheng
  • Kunqian Yu
  • Hong Liu
  • Xiaomin Luo
  • Kaixian Chen
  • Weiliang Zhu
  • Hualiang Jiang
Original Paper

DOI: 10.1007/s10822-006-9080-0

Cite this article as:
Zheng, M., Yu, K., Liu, H. et al. J Comput Aided Mol Des (2006) 20: 549. doi:10.1007/s10822-006-9080-0

Abstract

The recent wide spreading of the H5N1 avian influenza virus (AIV) in Asia, Europe and Africa and its ability to cause fatal infections in human has raised serious concerns about a pending global flu pandemic. Neuraminidase (NA) inhibitors are currently the only option for treatment or prophylaxis in humans infected with this strain. However, drugs currently on the market often meet with rapidly emerging resistant mutants and only have limited application as inadequate supply of synthetic material. To dig out helpful information for designing potent inhibitors with novel structures against the NA, we used automated docking, CoMFA, CoMSIA, and HQSAR methods to investigate the quantitative structure–activity relationship for 126 NA inhibitors (NIs) with great structural diversities and wide range of bioactivities against influenza A virus. Based on the binding conformations discovered via molecular docking into the crystal structure of NA, CoMFA and CoMSIA models were successfully built with the cross-validated q2 of 0.813 and 0.771, respectively. HQSAR was also carried out as a complementary study in that HQSAR technique does not require 3D information of these compounds and could provide a detailed molecular fragment contribution to the inhibitory activity. These models also show clearly how steric, electrostatic, hydrophobicity, and individual fragments affect the potency of NA inhibitors. In addition, CoMFA and CoMSIA field distributions are found to be in well agreement with the structural characteristics of the corresponding binding sites. Therefore, the final 3D-QSAR models and the information of the inhibitor–enzyme interaction should be useful in developing novel potent NA inhibitors.

Keywords

Avian influenzaNeuraminidase inhibitorDocking3D-QSARCoMFACoMSIAHQSAR

Copyright information

© Springer Science+Business Media, LLC 2006

Authors and Affiliations

  • Mingyue Zheng
    • 1
  • Kunqian Yu
    • 1
  • Hong Liu
    • 1
  • Xiaomin Luo
    • 1
  • Kaixian Chen
    • 1
  • Weiliang Zhu
    • 1
  • Hualiang Jiang
    • 1
  1. 1.Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia MedicaChinese Academy of SciencesShanghaiP.R. China