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.