Virtual screening (VS) is a powerful computational tool to guide the identification of new hits from large chemical libraries. This technique is widely used in drug discovery programs in pharmaceutical companies and in academia. There are two broad categories of screening techniques: ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS). The SBVS approach utilizes the knowledge of the 3D structure of the biological target in the process to select ligands with acceptable affinity and complementarity with the binding site. Therefore, SBVS can be done through docking calculations and binding affinity predictions as well as by structure-based pharmacophores. LBVS is the approach of choice when the biological target is not known or its 3D structure is not available. LBVS can be done by similarity search, ligand-based pharmacophores or QSAR (Quantitative Structure–Activity Relationship), for example. In OpenZika project, as we developed reliable homology models for the Zika proteins,1 we will use molecular docking as VS screening technique. Other previous success stories have shown that the use of VS approaches allow the reduction of the required time and costs for drug research and development and mitigate the risk for late stage failures. In silico techniques were crucial in the development of the HIV integrase inhibitor Raltegravir, the anticoagulant Tirofiban and the anti-influenza drug Zanamivir.2

1. Ekins, S.; Liebler, J.; Neves, B. J.; Lewis, W. G.; Coffee, M.; Bienstock, R.; Southan, C.; Andrade, C. H. Illustrating and Homology Modeling the Proteins of the Zika Virus. F1000Research 2016; 5 (0), 275. 10.12688/f1000research.8213.1

2. Glaab, E. Building a virtual ligand screening pipeline using free software: a survey Brief Bioinform, 2016; 17 (2): 352-366. 10.1093/bib/bbv037