Figure 1

Overview of functional site discovery approach. Starting from thousands of protein microenvironments, we use k-means clustering to group them into coarse clusters. Each coarse cluster is then hierarchically clustered, and optimal clusters are identified using a scoring function that incorporates knowledge from scientific literature. These clusters are annotated using information from literature, Swiss-Prot records, and PDB HETATM data to produce novel individual site annotations and potentially novel functional motifs.