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Fragment-based drug discovery (FBDD) has become a well-established and widely used approach for lead identification. The computational chemistry community has played a central role in developing the ideas behind this area of research and computational tools are important throughout FBDD campaigns. This article discusses the evolution of best practice, on-going areas of debate and gaps in current capabilities from a computational chemistry perspective. In particular, the contribution of computational methods to areas such as fragment library design, screening analysis, data handling and the role of structure- and ligand-based design is discussed. The potential to combine FBDD with other hit-identification methods such as high-throughput screening in a more integrated approach is also highlighted.

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