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Identification of small molecule inhibitors of pyruvate kinase M2.

ABSTRACT: A common feature of tumors arising from diverse tissue types is a reliance on aerobic glycolysis for glucose metabolism. This metabolic difference between cancer cells and normal cells could be exploited for therapeutic benefit in patients. Cancer cells universally express the M2 isoform of the glycolytic enzyme pyruvate kinase (PKM2), and previous work has demonstrated that PKM2 expression is necessary for aerobic glycolysis and cell proliferation in vivo. Because most normal tissues express an isoform of pyruvate kinase other than PKM2, selective targeting of PKM2 provides an opportunity to target cell metabolism for cancer therapy. PKM2 has an identical catalytic site as the related M1 splice variant (PKM1). However, isoform selective inhibition is possible as PKM2 contains a unique region for allosteric regulation. We have screened a library of greater than 1,00,000 small molecules to identify such inhibitors. The inhibitors identified for PKM2 fell primarily into three distinct structural classes. The most potent PKM2 inhibitor resulted in decreased glycolysis and increased cell death following loss of growth factor signaling. At least part of this effect was due to on-target PKM2 inhibition as less cell death was observed in cells engineered to express PKM1. These data suggest that isoform selective inhibition of PKM2 with small molecules is feasible and support the hypothesis that inhibition of glucose metabolism in cancer cells is a viable strategy to treat human malignancy.

SUBMITTER: Vander Heiden MG

PROVIDER: S-EPMC2823991 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature

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Identification of small molecule inhibitors of pyruvate kinase M2.

Vander Heiden Matthew G MG Christofk Heather R HR Schuman Eli E Subtelny Alexander O AO Sharfi Hadar H Harlow Edward E EE Xian Jun J Cantley Lewis C LC

Biochemical pharmacology 20091211 8

A common feature of tumors arising from diverse tissue types is a reliance on aerobic glycolysis for glucose metabolism. This metabolic difference between cancer cells and normal cells could be exploited for therapeutic benefit in patients. Cancer cells universally express the M2 isoform of the glycolytic enzyme pyruvate kinase (PKM2), and previous work has demonstrated that PKM2 expression is necessary for aerobic glycolysis and cell proliferation in vivo. Because most normal tissues express an ...[more]

PMID: 20005212

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Project description:Kinases are heavily pursued pharmaceutical targets because of their mechanistic role in many diseases. Small molecule kinase inhibitors (SMKIs) are a compound class that includes marketed drugs and compounds in various stages of drug development. While effective, many SMKIs have been associated with toxicity including chromosomal damage. Screening for kinase-mediated toxicity as early as possible is crucial, as is a better understanding of how off-target kinase inhibition may give rise to chromosomal damage. To that end, we employed a competitive binding assay and an analytical method to predict the toxicity of SMKIs. Specifically, we developed a model based on the binding affinity of SMKIs to a panel of kinases to predict whether a compound tests positive for chromosome damage. As training data, we used the binding affinity of 113 SMKIs against a representative subset of all kinases (290 kinases), yielding a 113x290 data matrix. Additionally, these 113 SMKIs were tested for genotoxicity in an in vitro micronucleus test (MNT). Among a variety of models from our analytical toolbox, we selected using cross-validation a combination of feature selection and pattern recognition techniques: Kolmogorov-Smirnov/T-test hybrid as a univariate filter, followed by Random Forests for feature selection and Support Vector Machines (SVM) for pattern recognition. Feature selection identified 21 kinases predictive of MNT. Using the corresponding binding affinities, the SVM could accurately predict MNT results with 85% accuracy (68% sensitivity, 91% specificity). This indicates that kinase inhibition profiles are predictive of SMKI genotoxicity. While in vitro testing is required for regulatory review, our analysis identified a fast and cost-efficient method for screening out compounds earlier in drug development. Equally important, by identifying a panel of kinases predictive of genotoxicity, we provide medicinal chemists a set of kinases to avoid when designing compounds, thereby providing a basis for rational drug design away from genotoxicity.

Dataset Information

Identification of small molecule inhibitors of pyruvate kinase M2.

Publications

Identification of small molecule inhibitors of pyruvate kinase M2.

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