Structural models for the design of novel antiviral agents against Greek Goat Encephalitis

PeerJ. 2014 Nov 6:2:e664. doi: 10.7717/peerj.664. eCollection 2014.

Abstract

The Greek Goat Encephalitis virus (GGE) belongs to the Flaviviridae family of the genus Flavivirus. The GGE virus constitutes an important pathogen of livestock that infects the goat's central nervous system. The viral enzymes of GGE, helicase and RNA-dependent RNA polymerase (RdRP), are ideal targets for inhibitor design, since those enzymes are crucial for the virus' survival, proliferation and transmission. In an effort to understand the molecular structure underlying the functions of those viral enzymes, the three dimensional structures of GGE NS3 helicase and NS5 RdRP have been modelled. The models were constructed in silico using conventional homology modelling techniques and the known 3D crystal structures of solved proteins from closely related species as templates. The established structural models of the GGE NS3 helicase and NS5 RdRP have been evaluated for their viability using a repertoire of in silico tools. The goal of this study is to present the 3D conformations of the GGE viral enzymes as reliable structural models that could provide the platform for the design of novel anti-GGE agents.

Keywords: Computational biology; Drug design; Flaviviridae; Greek Goat Encephalitis virus; Helicase; Homology modelling; Phylogenetic analysis; RNA-dependent RNA polymerase.

Grants and funding

This work was partially supported by The BIOEXPLORE research project, which falls under the Operational Program “Education and Lifelong Learning” and is co-financed by the European Social Fund (ESF) and National Resources and ESF and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF)—Research Funding Program: “Thales” Investing in knowledge society through the European Social Fund. The authors are members of the BM1006 COST Action, SeqAhead: Next Generation Sequencing Data Analysis Network. VLK is funded by a Marie Curie Intra European Fellowship within the 7th European Community Framework Programme. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.