Interactive Exploration of Sequence and Structural Data to Identify Functional Mutations in Protein Families
Timothy Luciani, John Wenskovitch, Koonwah Chen, David Koes, Tim Travers, G. Elisabeta Marai
We present the design and implementation of a visual mining and analysis tool to help identify protein mutations across family structural models, and to help discover the effect of these mutations on protein function. We follow a client-server approach in which distributed data sources for 3D structure and non-spatial sequence information are seamlessly integrated into a common visual interface. Multiple linked views and a computational backbone allow comparison at the molecular and atomic levels, while a trend-image visual abstraction allows for the sorting and mining of large collections of sequences and of their residues. We evaluate our tool on the triosephosphate isomerase (TIM) family structural models and sequence data, and show that our tool provides an effective, scalable way to navigate a family of proteins, as well as a means to inspect the structure and sequence of individual proteins.