Title: CoMFA, CoMSIA analysis of 4-[5-(4-Fluoro-benzyl-1H-pyrazol-3-yl]-pyridine derivatives as CYP3A4 inhibitors

Authors: Neelamma Mantri; Jaheer Mohmed; Seshagiri Bandi; G.H. Anuradha; Mounica Bandela

Addresses: Department of Chemistry, University College of Science, Osmania University, Hyderabad, Telangana, 500007, India ' Department of Chemistry, University College of Science, Osmania University, Hyderabad, Telangana, 500007, India ' Bioinformatics Division, PGRRCDE, Osmania University, Hyderabad, Telangana, 500007, India ' Department of Chemistry, University College of Science, Osmania University, Hyderabad, Telangana, 500007, India ' Bioinformatics Division, PGRRCDE, Osmania University, Hyderabad, Telangana, 500007, India

Abstract: 3-Dimensional Quantitative Structure-Activity Relationship (3D-QSAR) studies were performed on a series of 4-[5-(4-Fluoro-benzyl-1H-pyrazol-3-yl]-pyridine derivatives as CYP3A4 inhibitors. The molecular superimposition of most active compound structure was performed by atom/shape-based root mean square (RMS) fit. The statistically significant model was established from 95 molecules; which were validated by evaluation of test set of 24 compounds and training set of 71 compounds. The atom-based RMS alignment yielded best predictive comparative molecular field analysis (CoMFA) model q² = 0.784; r² = 0.974; F-value = 479.682 with five components; while the comparative molecular similarity indices analysis (CoMSIA) model yielded q² = 0.797; r² = 0.987; F-value = 791.297 with six components. Contour maps obtained from 3D-QSAR CoMFA; CoMSIA studies were evaluated for the biological activity trends of the molecules analysed. The statistical analysis results indicate that the steric; electrostatic; hydrogen bond donor and acceptor substituents play a significant role in CYP3A4 activity. The contribution of the ligand-based study approach is expected to become more significant and effective in the future.

Keywords: CYP3A4; 4-[5-(4-Fluoro-benzyl-1H-pyrazol-3-yl]-pyridine; CoMFA; comparative molecular field analysis; CoMSIA; comparative molecular similarity indices analysis.

DOI: 10.1504/IJCBDD.2017.085404

International Journal of Computational Biology and Drug Design, 2017 Vol.10 No.3, pp.225 - 236

Received: 08 Sep 2016
Accepted: 13 Feb 2017
Published online: 25 Jul 2017 *

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