Using networks to identify fine structural differences between functionally distinct protein states.

The vast increase in available data from the "-omics" revolution has enabled the fields of structural proteomics and structure prediction to make great progress in assigning realistic three-dimensional structures to each protein molecule. The challenge now lies in determining the fine structural details that endow unique functions to sequences that assume a common fold. Similar problems are encountered in understanding how distinct conformations contribute to different phases of a single protein's dynamic function. However, efforts are hampered by the complexity of these large, three-dimensional molecules. To overcome this limitation, structural data have been recast as two-dimensional networks. This analysis greatly reduces visual complexity but retains information about individual residues. Such diagrams are very useful for comparing multiple structures, including (1) homologous proteins, (2) time points throughout a dynamics simulation, and (3) functionally different conformations of a given protein. Enhanced structural examination results in new functional hypotheses to test experimentally. Here, network representations were key to discerning a difference between unliganded and inducer-bound lactose repressor protein (LacI), which were previously presumed to be identical structures. Further, the interface of unliganded LacI was surprisingly similar to that of the K84L variant and various structures generated by molecular dynamics simulations. Apo-LacI appears to be poised to adopt the conformation of either the DNA- or inducer-bound structures, and the K84L mutation appears to freeze the structure partway through the conformational transition. Additional examination of the effector binding pocket results in specific hypotheses about how inducer, anti-inducer, and neutral sugars exert their effects on repressor function.