This project is part of a long-standing collaboration with the laboratory of Dr. Ettore Appella (LCB/NCI), in which the Wip1 protein was discovered. Initial characterization resulted in determining two classes of phosphorylated substrates, involving many proteins involved in cell growth regulation. The first has a diphosphorylated sequence motif (pT-X-pY), such as in p38 MAP Kinase, while the second has a mono-phosphorylated sequence motif (p(S/T)Q), such as in the p53, Chk1/2 and ATM proteins. By development of an atomic-scale computer model of the extended active site of Wip1 and a series of mutagenesis experiments, we were able to reveal the structural basis for the range of substrate specificity. This lead to the development of a cyclic peptide molecule that competitively inhibits Wip1, the first inhibitor of any kind for this family of enzymes. We then pursued development of a more drug-like, small molecule inhibitor in collaboration with Dr. Daniel Appella (LBC/NIDDK), who specializes in synthetic chemistry. The resultant small molecule is based on a pyrrole ring scaffold, with 5 different emanating sidechains to mimic the amino acids of the cyclic peptide. While successful, the final inhibition constant was still only in the low micromolar range. To further this effort, this last year we returned to optimizing the cyclic peptide inhibitor. By multiple iterations of design and testing, we were able to drastically increase the binding affinity, resulting in an inhibition constant of 110 nM. The structural modeling involved in this process revealed both important new interactions in the extended active site, and the role of the proximal B-loop in binding substrate and regulating activity. Since the B-loop is unique to the Wip1 member of the PP2C family, its role was previously unknown. We are now applying these lessons to designing a new generation of pyrrole-based inhibitors. We are also pursuing generating sufficient Wip1 protein to determine the structure by X-ray crystallography, which will greatly aid in inhibitor optimization.