A key aspect of efficient scientific research is the efficient accumulation, exchange and
presentation of relevant information. Multi-disciplinary fields of research, such as structure-based lead
discovery (SBLD), depend upon many different data types and require the concurrent capture and
display of such heterogeneous types of data. The visualisation of such data in a more intuitive and
accessible format than the underlying data capture method is often extended to provide the viewer
context within a wider range of data types. In the field of SBLD, experimental protein structure
determination presents a need to visualise three-dimensional data and to further annotate such
visualisations with additional information. The use of high-throughput methods in both chemistry and
biology has resulted in a rapid accumulation of relevant information to support and prioritise SBLD.
The appropriate integration and visualisation of this data maximises the impact of the underlying
information within the context of a project both not only for computational chemists and structural
biologists but also for biologists and medicinal chemists. In this chapter we will discuss current
approaches and outstanding issues associated with this particular challenge in the context of SBLD.
