Pointer Advanced in silico approaches in antiviral research

Computer-aided drug design has seen constantly increasing application over the past two decades in every area of drug discovery. It can offer significant advantages over conventional approaches, being far less expensive and faster than conventional methods, or offering the possibility to predict molecular behaviours that cannot be elucidated in any other way. Recent developments in software and hardware make it possible to simulate increasingly complex molecular environments, widening the applicability of in silico studies from the interactions of small molecules with key protein residues, to the simulation of the dynamic evolution of complex biological systems with atomic resolution. Antiviral research offers several open challenges, from a biological, biochemical and pharmaceutical point of view. Computational approaches are already providing some answers and will undoubtedly give more in the near future. Here, we present a brief overview of the cutting-edge computational methods that play a major role in present and future antiviral research. Molecular modelling techniques have been playing an increasingly crucial role in the search for new drugs and their optimization, in every area of drug design. Although they were initially confined to the visualization of potential drug interactions in targeted enzyme binding, these techniques are now being applied by many research groups worldwide as a powerful tool to help define the relationship between biological activities, binding geometries and mechanisms of action in physiological or pathological processes. This is clear from the increasing number of literature sources concerned with in silico approaches and the boost in the number of molecular modelling packages, both commercial and non- commercial, available to researchers [1]. The reason for this boost is threefold: the improvement in the mathematical models that describe chemical phenomena, which grants higher-precision results; the increase in the number of proteins with known threedimensional (3D) structure solved through crystallographic or NMR experiments; and the development of cheaper and more powerful hardware. Moreover, the adoption of more intuitive programme interfaces and ergonomic devices, such as haptic styli, has increased the interactivity of the user with the machines [2]. The large range of applications that computer-aided drug design (CADD) methods have acquired confirms that CADD techniques will play a role of increasing importance in drug discovery in the future. The current