Mitogen-activated protein kinase phosphatase-1 (MKP-1) is a dual specificity phosphatase that is overexpressed in many human tumors and can protect cells from apoptosis caused by DNA-damaging agents or cellular stress. Small molecule inhibitors of MKP-1 have not been reported, in part because of the lack of structural guidance for inhibitor design and definitive assays for MKP-1 inhibition in intact cells. Herein we have exploited a high content chemical complementation assay to analyze a diverse collection of pure natural products for cellular MKP-1 inhibition. Using two-dimensional Kolmogorov-Smirnov statistics, we identified sanguinarine, a plant alkaloid with known antibiotic and antitumor activity but no primary cellular target, as a potent and selective inhibitor of MKP-1. Sanguinarine inhibited cellular MKP-1 with an IC50 of 10 microM and showed selectivity for MKP-1 over MKP-3. Sanguinarine also inhibited MKP-1 and the MKP-1 like phosphatase, MKP-L, in vitro with IC50 values of 17.3 and 12.5 microM, respectively, and showed 5-10-fold selectivity for MKP-3 and MKP-1 over VH-1-related phosphatase, Cdc25B2, or protein-tyrosine phosphatase 1B. In a human tumor cell line with high MKP-1 levels, sanguinarine caused enhanced ERK and JNK/SAPK phosphorylation. A close congener of sanguinarine, chelerythrine, also inhibited MKP-1 in vitro and in whole cells, and activated ERK and JNK/SAPK. In contrast, sanguinarine analogs lacking the benzophenanthridine scaffold did not inhibit MKP-1 in vitro or in cells nor did they cause ERK or JNK/SAPK phosphorylation. These data illustrate the utility of a chemical complementation assay linked with multiparameter high content cellular screening.

Presently, the zebrafish is the only vertebrate model compatible with contemporary paradigms of drug discovery. Zebrafish embryos are amenable to automation necessary for high‐throughput chemical screens, and optical transparency makes them potentially suited for image‐based screening. However, the lack of tools for automated analysis of complex images presents an obstacle to using the zebrafish as a high‐throughput screening model. We have developed an automated system for imaging and analyzing zebrafish embryos in multi‐well plates regardless of embryo orientation and without user intervention. Images of fluorescent embryos were acquired on a high‐content reader and analyzed using an artificial intelligence‐based image analysis method termed Cognition Network Technology (CNT). CNT reliably detected transgenic fluorescent embryos (Tg(fli1:EGFP)^y1) arrayed in 96‐well plates and quantified intersegmental blood vessel development in embryos treated with small molecule inhibitors of anigiogenesis. The results demonstrate it is feasible to adapt image‐based high‐content screening methodology to measure complex whole organism phenotypes. Developmental Dynamics 238:656–663, 2009.