3D-QSAR studies of indole derivatives as phosphodiesterase IV inhibitors

Chakraborti, Asit K., Gopalakrishnan, B., Sobhia, M. Elizabeth and Malde, Alpeshkumar (2003) 3D-QSAR studies of indole derivatives as phosphodiesterase IV inhibitors. European Journal of Medicinal Chemistry, 38 11-12: 975-982. doi:10.1016/j.ejmech.2003.09.001


Author Chakraborti, Asit K.
Gopalakrishnan, B.
Sobhia, M. Elizabeth
Malde, Alpeshkumar
Title 3D-QSAR studies of indole derivatives as phosphodiesterase IV inhibitors
Journal name European Journal of Medicinal Chemistry   Check publisher's open access policy
ISSN 0223-5234
Publication date 2003-12-01
Sub-type Article (original research)
DOI 10.1016/j.ejmech.2003.09.001
Volume 38
Issue 11-12
Start page 975
End page 982
Total pages 8
Place of publication Paris
Publisher S.E.C.T.
Language eng
Subject 030404 Cheminformatics and Quantitative Structure-Activity Relationships
030401 Biologically Active Molecules
Abstract The 3D-QSAR studies of some indole derivatives as phosphodiesterase (PDE) type IV inhibitors was performed by Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods to determine the factors required for the activity of these compounds. The global minimum energy conformer of the template molecule, 3 the most active molecule of the series, was obtained by simulated annealing method and used to build the structures of the molecules in the dataset. The CoMFA model produced statistically significant results with cross-validated and conventional correlation coefficients of 0.494 and 0.986 respectively. The combination of steric, electrostatic and hydrophobic fields in CoMSIA gave the best results with cross-validated and conventional correlation coefficients of 0.541 and 0.967 respectively. The predictive ability of CoMFA and CoMSIA were determined using a test set of seven indole derivatives giving predictive correlation coefficients of 0.56 and 0.59 respectively indicating good predictive power. Further, the robustness of the models was verified by bootstrapping analysis. Based upon the information derived from CoMFA and CoMSIA, we have identified some key features that may be used to design new indole derivatives and predict their PDE IV affinities prior to synthesis.
Keyword PDE IV inhibitors
anti-asthma
3D-QSAR
CoMFA
CoMSIA
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Unknown

Document type: Journal Article
Sub-type: Article (original research)
Collections: Excellence in Research Australia (ERA) - Collection
School of Chemistry and Molecular Biosciences
 
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