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Issue 3, 2013
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Inhibition mechanism exploration of quinoline derivatives as PDE10A inhibitors by in silico analysis

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Abstract

As a potential target for the treatment of schizophrenia, the dual cAMP/cGMP hydrolyzing enzyme PDE10A has attracted a significant amount of attention. In the present work, the inhibition mechanism of 116 structurally diverse quinoline derivatives as PDE10A inhibitors was explored by 3D-QSAR, molecular docking and molecular dynamics (MD) simulations. The QSAR models based on the training set containing 88 molecules were established by using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The resultant optimum CoMSIA model showed strong predictability with a Q2 of 0.497, an Rncv2 of 0.964 and an Rpre2 of 0.885. Furthermore, there was good consistency between the CoMSIA model, docking and MD results. Our findings are: (1) bulky substituents at the 8-position and ring D increase the biological activity. (2) The areas around the 14-position and ring D are the electrostatic and hydrophobic sensitive regions. (3) H-bonds, π–π stacking interactions and hydrophobic contacts are crucial in determining the binding affinity to PDE10A. (4) The six-membered heterocyclic group at ring D, especially a heterobenzene ring, containing the atom as an H-bond acceptor at the 18-position is essential to water-mediated H-bond networks and favorable in enhancing the inhibitory potency. These models and the derived information may help to provide better understanding of the interaction mechanism of PDE10A inhibitors and to facilitate lead optimization and novel inhibitors' design.

Graphical abstract: Inhibition mechanism exploration of quinoline derivatives as PDE10A inhibitors by in silico analysis

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Supplementary files

Article information


Submitted
06 Nov 2012
Accepted
07 Jan 2013
First published
09 Jan 2013

Mol. BioSyst., 2013,9, 386-397
Article type
Paper

Inhibition mechanism exploration of quinoline derivatives as PDE10A inhibitors by in silico analysis

Q. Wu, Q. Gao, H. Guo, D. Li, J. Wang, W. Gao, C. Han, Y. Li and L. Yang, Mol. BioSyst., 2013, 9, 386
DOI: 10.1039/C2MB25501D

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