An updated evolutionary study of Flaviviridae NS3 helicase and NS5 RNA-dependent RNA polymerase reveals novel invariable motifs as potential pharmacological targets.

The rate of Flaviviridae family virus infections worldwide has increased dramatically in the last few years. In addition, infections caused by arthropod vector viruses including Hepatitis C, West Nile, Dengue fever, Yellow fever and Japanese encephalitis are emerging throughout the world. Based on a recent taxon update, the Flaviviridae family comprises four main genera; Flavivirus, Hepacivirus, Pestivirus and a recent genus Pegivirus. Although the new scientific classification plays a key role in providing useful information about the relationships between viruses, many new documented viruses remain unclassified. Furthermore, based on the different results of several studies the classification is unclear. In an effort to provide more insights into the classification of viruses, a holistic evolutionary study of the two viral enzymes NS3 helicase and NS5 RNA-dependent RNA polymerase (RdRp) has been conducted in this study. These two viral enzymes are very crucial for the inhibition of viruses due to the fact that they are involved in the survival, proliferation and transmission of viruses. The main goal of this study is the presentation of two novel updated phylogenetic trees of the enzymes NS3 helicase and NS5 RdRp as a reliable phylogeny "map" to correlate the information of the closely related viruses and identify new possible targets for the Flaviviridae family virus inhibition. Despite the earliest trials for drugs against Flaviviridae related viruses, no antiviral drug vaccine has been available to date. Therefore there is an urgent need for research towards the development of efficient antiviral agents.

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

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.

Molecular dynamics simulations through GPU video games technologies.

Bioinformatics is the scientific field that focuses on the application of computer technology to the management of biological information. Over the years, bioinformatics applications have been used to store, process and integrate biological and genetic information, using a wide range of methodologies. One of the most de novo techniques used to understand the physical movements of atoms and molecules is molecular dynamics (MD). MD is an in silico method to simulate the physical motions of atoms and molecules under certain conditions. This has become a state strategic technique and now plays a key role in many areas of exact sciences, such as chemistry, biology, physics and medicine. Due to their complexity, MD calculations could require enormous amounts of computer memory and time and therefore their execution has been a big problem. Despite the huge computational cost, molecular dynamics have been implemented using traditional computers with a central memory unit (CPU). A graphics processing unit (GPU) computing technology was first designed with the goal to improve video games, by rapidly creating and displaying images in a frame buffer such as screens. The hybrid GPU-CPU implementation, combined with parallel computing is a novel technology to perform a wide range of calculations. GPUs have been proposed and used to accelerate many scientific computations including MD simulations. Herein, we describe the new methodologies developed initially as video games and how they are now applied in MD simulations.