Development and application of tools for structure-based library design.

摘要

Three-dimensional protein structures contain a formidable amount of information. The function of a protein is largely encoded in the structure. The scope of possible inhibitors is also dictated by the structure. More indirectly, the structure of related proteins can be inferred through comparative modeling. In the course of studying two enzyme families, the serine proteases and the sulfotransferases, all three of these types of analyses were performed.; Much of the structural basis for serine protease specificity of serine proteases has previously been worked out, but surprises are still emerging. The structure of β-tryptase is an unusual tetrameric ring, and docking of an optimal substrate sequence reveals a role for this structure in determining substrate specificity. The mouse and human versions of granzyme A have very similar sequences, but a striking difference in substrate specificity is observed. Molecular docking reveals a possible reason for this difference by predicting a difference in substrate binding mode between the two homologs.; In the area of inhibitor design, methods to interface molecular docking with combinatorial chemistry were developed and tested. Improved methods to position the scaffold of a combinatorial library and choose substituents were validated using a set of thermodynamic data for macromolecular serine protease inhibitors. This method was then applied to the design of two libraries directed against sulfotransferase enzymes, and the libraries have subsequently been shown to contain inhibitors of multiple sulfotransferases.; Finally, comparative models were built in cases where structures of the proteins of interest were not available. In the case of granzyme A the models revealed possible structural determinants of the specificity difference between the mouse and human homologs. Local comparative modeling of the nucleotide-binding site in several families of sulfotransferases showed differences between the families that may impact both catalytic mechanism and inhibitor design.