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Letters in Drug Design & Discovery

Editor-in-Chief

ISSN (Print): 1570-1808
ISSN (Online): 1875-628X

Research Article

Computational Studies of N-substituted Quinolinonyl Diketo Acid Derivatives as HIV Integrase Strand Transfer Inhibitors using 3D-QSAR, Pharmacophore Modeling and Molecular Docking

Author(s): Yuming Luo, Yujie Ren* and Xiaodong Gao

Volume 14 , Issue 11 , 2017

Page: [1291 - 1302] Pages: 12

DOI: 10.2174/1570180814666170605120017

Price: $65

Abstract

Background: Acquired immunodeficiency syndrome is a disease derive from infection of human immunodeficiency virus, and integrase is an important target for antiviral drugs. Nsubstituted quinolinonyl diketo acid derivatives as integrase strand transfer inhibitors were investigated in this work to discuss the relationships between chemical structures and their bioactivities.

Methods: Three-dimensional quantitative structure-activity relationship, pharmacophore, and molecular docking simulations as computational chemistry tools are used in this study. The crystal structure of receptors and ligands from protein data bank are also employed.

Results: The structure-activity relationship models with statistically significant parameters are built, and molecular docking simulation is performed to show the rational interaction of the receptor and ligand. Besides, the pharmacophore model generated by four potent integrase inhibitors find the important features which are crucial to the inhibitory activities.

Conclusion: In this series of compounds, the modification of hydrophobic and electronegative substituents in benzene ring would be benefit for the inhibitory activity against integrase strand transfer. The hydrophobic interactions and chelating interactions are found in docking simulation result between receptor and ligand, which indicate the importance of diketo acid chain and quinolinonyl moiety. All the results could serve as basis for the development of potential integrase inhibitors.

Keywords: 3D-QSAR, molecular docking, integrase strand transfer inhibitors, pharmacophore modeling, AIDs, FDA.

Graphical Abstract

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