Computationally supported development of small molecule inhibitors has successfully been applied to protein tyrosine phosphatases in the past, revealing a number of cell-active compounds. Similar approaches have also been used to screen for small molecule inhibitors for the cancer-related phosphatases of regenerating liver (PRL) family. Still, selective and cell-active compounds are of limited availability. Since especially PRL-3 remains an attractive drug target due to its clear role in cancer metastasis, such compounds are highly demanded. In this study, we investigated various virtual screening approaches for their applicability to identify novel small molecule entities for PRL-3 as target. Biochemical evaluation of purchasable compounds revealed ligand-based approaches as well suited for this target, compared to docking-based techniques that did not perform well in this context. The best hit of this study, a 2-cyano-2-ene-ester and hence a novel chemotype targeting the PRLs, was further optimized by a structure–activity-relationship (SAR) study, leading to a low micromolar PRL inhibitor with acceptable selectivity over other protein tyrosine phosphatases. The compound is active in cells, as shown by its ability to specifically revert PRL-3 induced cell migration, and exhibits similar effects on PRL-1 and PRL-2. It is furthermore suitable for fluorescence microscopy applications, and it is commercially available. These features make it the only purchasable, cell-active and acceptably selective PRL inhibitor to date that can be used in various cellular applications.
Metabolite binding to proteins regulates nearly all cellular processes, but our knowledge of these interactions originates primarily from empirical
in vitro
studies. Here, we report the first systematic study of interactions between water‐soluble proteins and polar metabolites in an entire biological subnetwork. To test the depth of our current knowledge, we chose to investigate the well‐characterized
Escherichia coli
central metabolism. Using ligand‐detected
NMR
, we assayed 29 enzymes towards binding events with 55 intracellular metabolites. Focusing on high‐confidence interactions at a false‐positive rate of 5%, we detected 98 interactions, among which purine nucleotides accounted for one‐third, while 50% of all metabolites did not interact with any enzyme. In contrast, only five enzymes did not exhibit any metabolite binding and some interacted with up to 11 metabolites. About 40% of the interacting metabolites were predicted to be allosteric effectors based on low chemical similarity to their target's reactants. For five of the eight tested interactions,
in vitro
assays confirmed novel regulatory functions, including
ATP
and
GTP
inhibition of the first pentose phosphate pathway enzyme. With 76 new candidate regulatory interactions that have not been reported previously, we essentially doubled the number of known interactions, indicating that the presently available information about protein–metabolite interactions may only be the tip of the iceberg.
Cells respond to stress by blocking translation, rewiring metabolism, and forming transient mRNP assemblies called stress granules (SGs). After stress release, re-establishing homeostasis requires energy-consuming processes. However, the molecular mechanisms whereby cells restore energy production to disassemble SGs and reinitiate growth after stress remain poorly understood. Here we show that, upon stress, the ATP-producing enzyme Cdc19 forms inactive amyloids, and that their rapid re-solubilization is essential to restore energy production and disassemble SGs. Cdc19 re-solubilization is initiated by the glycolytic metabolite fructose-1,6-bisphosphate (FBP), which directly binds Cdc19 amyloids and facilitates conformational changes that allow Hsp104 and Ssa2 chaperone recruitment. FBP then promotes Cdc19 tetramerization, which boosts its activity to further enhance ATP production and SG disassembly. Together, these results describe a molecular mechanism essential for stress recovery, which directly couples metabolism with SG dynamics via regulation of Cdc19 amyloids.
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