Epitopes based drug design for dengue virus envelope protein: A computational approach. (December 2017)

• Record Type: Journal Article
• Authors: Wadood, Abdul; Mehmood, Aamir; Khan, Huma; Ilyas, Muhammad; Ahmad, Ayaz; Alarjah, Mohammed; Abu-Izneid, Tareq
• Is Part Of: Computational biology and chemistry. Volume 71(2017)
• Page Start: 152
• Page End: 160
• Publication Date: 2017-12
• Subjects: Dengue virus -- Epitope -- Envelope protein -- Molecular docking -- Virtual screening; 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.2017.10.008
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: A conserved region "QHGTI" in B and T cell epitopes of dengue envelope glycoprotein was predicted. A reverse pharmacophore mapping approach was used to develop phamacophore model. ChemBridge database of compounds was screen on the basis of developed pharmacophopre model. The shortlisted compounds were docked and their interactions were explored. Finally, 14 compounds were reported as promising drug candidates for the treatment of dengue virus infection. Abstract: Dengue virus (DENV) has emerged as a rapidly spreading epidemic throughout the tropical and subtropical regions around the globe. No suitable drug has been designed yet to fight against DENV, therefore, the need for safe and effective antiviral drug has become imperative. The envelope protein of DENV is responsible for mediating the fusion process between viral and host membranes. This work reports an in silico approach to target B and T cell epitopes for dengue envelope protein inhibition. A conserved region "QHGTI" in B and T cell epitopes of dengue envelope glycoprotein was confirmed to be valid for targeting by visualizing its interactions with the host cell membrane TIM-1 protein which acts as a receptor for serotype 2 and 3. A reverse pharmacophore mapping approach was used to generate a seven featured pharmacophore model on the basis of predicted epitope. This pharmacophore model as a 3D query was used to virtually screen a chemical compounds dataset "Chembridge". A total of 1010 compounds mapped on the developed pharmacophore model. These retrieved hits were subjected to filtering via Lipinski's rule of five, as a result 442 molecules were shortlisted for further assessment using molecular docking. Finally, 14 hits of different structural properties having interactions with the active site residues of dengue envelope glycoprotein were selected as lead candidates. These structurally diverse lead candidates have strong likelihood to act as further starting structures in the development of novel and potential drugs for the treatment of dengue fever.