Microscopic binding of butyrylcholinesterase with quinazolinimine derivatives and the structure-activity correlation

Mohamed Diwan M. AbdulHameed, Junjun Liu, Yongmei Pan, Lei Fang, Carlos Silva-Rivera, Chang Guo Zhan

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Butyrylcholinesterase (BChE) is not only an important protein for development of anti-cocaine medication but also an established drug target to develop new treatment for Alzheimer's disease (AD). The molecular basis of interaction of a new series of quinazolinimine derivatives as BChE inhibitors has been studied by molecular docking and molecular dynamics (MD) simulations. The molecular docking and MD simulations revealed that all of these inhibitors bind with BChE in similar binding mode. Based on the similar binding mode, we have carried out three-dimensional quantitative structure-activity relationship (3D-QSAR) studies on these inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), to understand the structure-activity correlation of this series of inhibitors and to develop predictive models that could be used in the design of new inhibitors of BChE. The study has resulted in satisfactory 3D-QSAR models. We have also developed ligand-based 3D-QSAR models. The contour maps obtained from the 3D-QSAR models in combination with the simulated binding structures help to better interpret the structure-activity relationship and is consistent with available experimental activity data. The satisfactory 3D-QSAR models strongly suggest that the determined BChE-inhibitor binding modes are reasonable. The identified binding modes and developed 3D-QSAR models for these BChE inhibitors are expected to be valuable for rational design of new BChE inhibitors that may be valuable in the treatment of Alzheimer's disease.

Original languageEnglish
Pages (from-to)69-82
Number of pages14
JournalTheoretical Chemistry Accounts
Issue number1
StatePublished - Sep 2011

Bibliographical note

Funding Information:
The research was supported by NIH (grant R01 DA013930 to CGZ). CSR worked in CGZ’s laboratory as a NIDA Summer Research Fellow (from School of Informatics, Indiana University) through a supplemental award (R01 DA013930-06S2 to CGZ). The authors also acknowledge the Center for Computational Sciences (CCS) at University of Kentucky for supercomputing time on IBM X-series Cluster with 340 nodes or 1,360 processors.


  • Binding mode
  • Butyrylcholinesterase
  • Inhibitor
  • Modeling

ASJC Scopus subject areas

  • Physical and Theoretical Chemistry


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