Multiple Ras proteins, including N-Ras, depend on a palmitoylation/depalmitoylation cycle to regulate their subcellular trafficking and oncogenicity. General lipase inhibitors such as Palmostatin M (Palm M) block N-Ras depalmitoylation, but lack specificity and target several enzymes displaying depalmitoylase activity. Here, we describe ABD957, a potent and selective covalent inhibitor of the ABHD17 family of depalmitoylases, and show that this compound impairs N-Ras depalmitoylation in human acute myeloid leukemia (AML) cells. ABD957 produced partial effects on N-Ras palmitoylation compared with Palm M, but was much more selective across the proteome, reflecting a plasma membrane-delineated action on dynamically palmitoylated proteins. Finally, ABD957 impaired N-Ras signaling and the growth of NRAS-mutant AML cells in a manner that synergizes with MAP kinase kinase (MEK) inhibition. Our findings uncover a surprisingly restricted role for ABHD17 enzymes as regulators of the N-Ras palmitoylation cycle and suggest that ABHD17 inhibitors may have value as targeted therapies for NRAS-mutant cancers.
Phenotype-based small-molecule screening is a powerful method to identify molecules that regulate cellular functions. However, such screens are generally performed in vitro under conditions that do not necessarily model complex physiological conditions or disease states. Here, we use molecular cell barcoding to enable direct in vivo phenotypic screening of small-molecule libraries. The multiplexed nature of this approach allows rapid in vivo analysis of hundreds to thousands of compounds. Using this platform, we screened >700 covalent inhibitors directed toward hydrolases for their effect on pancreatic cancer metastatic seeding. We identified multiple hits and confirmed the relevant target of one compound as the lipase ABHD6. Pharmacological and genetic studies confirmed the role of this enzyme as a regulator of metastatic fitness. Our results highlight the applicability of this multiplexed screening platform for investigating complex processes in vivo.
Lysophosphatidylserines (lyso-PSs) are a class of signaling lipids that regulate immunological and neurological processes. The metabolism of lyso-PSs remains poorly understood in vivo. Recently, we determined that ABHD12 is a major brain lyso-PS lipase, implicating lyso-PSs in the neurological disease polyneuropathy, hearing loss, ataxia, retinitis pigmentosa and cataract (PHARC), which is caused by null mutations in the ABHD12 gene. Here, we couple activity-based profiling with pharmacological and genetic methods to annotate the poorly characterized enzyme ABHD16A as a phosphatidylserine (PS) lipase that generates lyso-PS in mammalian systems. We describe a small-molecule inhibitor of ABHD16A that depletes lyso-PSs from cells, including lymphoblasts derived from subjects with PHARC. In mouse macrophages, disruption of ABHD12 and ABHD16A respectively increases and decreases both lyso-PSs and lipopolysaccharide-induced cytokine production. Finally, Abhd16a(-/-) mice have decreased brain lyso-PSs, which runs counter to the elevation in lyso-PS in Abhd12(-/-) mice. Our findings illuminate an ABHD16A-ABHD12 axis that dynamically regulates lyso-PS metabolism in vivo, designating these enzymes as potential targets for treating neuroimmunological disorders.
Title: Activity-based protein profiling for biochemical pathway discovery in cancer Nomura DK, Dix MM, Cravatt BF Ref: Nat Rev Cancer, 10:630, 2010 : PubMed
Large-scale profiling methods have uncovered numerous gene and protein expression changes that correlate with tumorigenesis. However, determining the relevance of these expression changes and which biochemical pathways they affect has been hindered by our incomplete understanding of the proteome and its myriad functions and modes of regulation. Activity-based profiling platforms enable both the discovery of cancer-relevant enzymes and selective pharmacological probes to perturb and characterize these proteins in tumour cells. When integrated with other large-scale profiling methods, activity-based proteomics can provide insight into the metabolic and signalling pathways that support cancer pathogenesis and illuminate new strategies for disease diagnosis and treatment.
