Computational insight into dengue virus NS2B-NS3 protease inhibition: A combined ligand- and structure-based approach. (December 2018)

• Record Type: Journal Article
• Authors: Chen, Junning; Jiang, Hailun; Li, Fangfei; Hu, Baichun; Wang, Ying; Wang, MingXing; Wang, Jian; Cheng, Maosheng
• Is Part Of: Computational biology and chemistry. Volume 77(2018)
• Page Start: 261
• Page End: 271
• Publication Date: 2018-12
• Subjects: Dengue -- NS2B-NS3 protease -- Molecular docking -- Pharmacophore models; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2018.09.010
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: The relationship between structure and activities of inhibitors was studied with a computational approach firstly. Molecular docking was employed to explore the specific allosteric site for non-peptidic inhibitors to bind. This research provided an accurate binding model for the discovery and optimization of NS2B-NS3 protease inhibitors. Abstract: The NS2B-NS3 protease is essential for the replication process of Dengue Virus, which make it an attractive target for anti-virus drugs. Since a considerable number of NS2B-NS3 protease inhibitors have been reported so far, it is significant for the discovery of more effective antivirus compounds with the essential structure-activity relationship extracted from known inhibitors. In this perspective, the relationship between the chemical features of inhibitors and their biological activities was investigated with a combined ligand- and structure-based approach. Furthermore, 3D pharmacophore models were generated with the best selected, which consisted of five chemical features: one ring aromatic group, one hydrophobic group, one hydrogen bond donor and two hydrogen bond acceptors (RHDAA). Subsequently, molecular docking was employed to explore the specific allosteric site for non-peptidic inhibitors to bind, which was proved to be located behind the catalytic triad. Taken the results of both molecular docking and pharmacophore modeling into consideration, a model of receptor-ligand interaction was obtained with four essential chemical features including aromatic rings and hydrogen bonds. This research provided an accurate binding model for the discovery and optimization of NS2B-NS3 protease inhibitors.