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Identification of a kinase profile that predicts chromosome damage induced by small molecule kinase inhibitors.

ABSTRACT: 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.

SUBMITTER: Olaharski AJ

PROVIDER: S-EPMC2704959 | biostudies-literature | 2009 Jul

REPOSITORIES: biostudies-literature

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Identification of a kinase profile that predicts chromosome damage induced by small molecule kinase inhibitors.

Olaharski Andrew J AJ Gonzaludo Nina N Bitter Hans H Goldstein David D Kirchner Stephan S Uppal Hirdesh H Kolaja Kyle K

PLoS computational biology 20090724 7

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 chromo ...[more]

PMID: 19629159

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Project description:ERBB2 amplification and overexpression are strongly associated with invasive cancer with high recurrence and poor prognosis. Enhanced ErbB2 signaling induces cysteine cathepsin B and L expression leading to their higher proteolytic activity (zFRase activity), which is crucial for the invasion of ErbB2-positive breast cancer cells in vitro. Here we introduce a simple screening system based on zFRase activity as a primary readout and a following robust invasion assay and lysosomal distribution analysis for the identification of compounds that can inhibit ErbB2-induced invasion. With an unbiased kinase inhibitor screen, we identified Bohemine/Roscovitine, Gö6979 and JAK3 inhibitor VI as compounds that can efficiently decrease cysteine cathepsin activity. Using the well-established and clinically relevant ErbB1 and ErbB2 inhibitor lapatinib as a positive control, we studied their ability to inhibit ErbB2-induced invasion in 3-dimensional Matrigel cultures. We found one of them, JAK3 inhibitor VI, capable of inhibiting invasion of highly invasive ErbB2-positive ovarian cancer cells as efficiently as lapatinib, whereas Gö6979 and Roscovitine displayed more modest inhibition. All compounds reversed the malignant, ErbB2-induced and invasion-supporting peripheral distribution of lysosomes. This effect was most evident for lapatinib and JAK3 inhibitor VI and milder for Gö6979 and Roscovitine. Our results further showed that JAK3 inhibitor VI function was independent of JAK kinases but involved downregulation of cathepsin L. We postulate that the screening method and the verification experiments that are based on oncogene-induced changes in lysosomal hydrolase activity and lysosomal distribution could be used for identification of novel inhibitors of ErbB2-induced invasiveness. Additionally, we introduce a novel function for lapatinib in controlling malignant lysosomal distribution, that may also be involved in its capability to inhibit ErbB2-induced invasion in vivo.

Project description:Background and Aim: More than half of the small-molecule kinase inhibitors (KIs) induced liver injury clinically. Meanwhile, studies have shown a close relationship between mitochondrial damage and drug-induced liver injury (DILI). We aimed to study KIs and the binding between drugs and mitochondrial proteins to find factors related to DILI occurrence. Methods: A total of 1,223 oral FDA-approved drugs were collected and analyzed, including 44 KIs. Fisher's exact test was used to analyze DILI potential and risk of different factors. A total of 187 human mitochondrial proteins were further collected, and high-throughput molecular docking was performed between human mitochondrial proteins and drugs in the data set. The molecular dynamics simulation was used to optimize and evaluate the dynamic binding behavior of the selected mitochondrial protein/KI complexes. Results: The possibility of KIs to produce DILI is much higher than that of other types (OR = 46.89, p = 9.28E-13). A few DILI risk factors were identified, including molecular weight (MW) between 400 and 600, the defined daily dose (DDD) ≥ 100 mg/day, the octanol-water partition coefficient (LogP) ≥ 3, and the degree of liver metabolism (LM) more than 50%. Drugs that met this combination of rules were found to have a higher DILI risk than controls (OR = 8.28, p = 4.82E-05) and were more likely to cause severe DILI (OR = 8.26, p = 5.06E-04). The docking results showed that KIs had a significant higher affinity with human mitochondrial proteins (p = 4.19E-11) than other drug types. Furthermore, the five proteins with the lowest docking score were selected for molecular dynamics simulation, and the smallest fluctuation of the backbone RMSD curve was found in the protein 5FS8/KI complexes, which indicated the best stability of the protein 5FS8 bound to KIs. Conclusions: KIs were found to have the highest odds ratio of causing DILI. MW was significantly related to the production of DILI, and the average docking scores of KI drugs were found to be significantly different from other classes. Further analysis identified the top binding mitochondrial proteins for KIs, and specific binding sites were analyzed. The optimization of molecular docking results by molecular dynamics simulation may contribute to further studying the mechanism of DILI.

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Identification of a kinase profile that predicts chromosome damage induced by small molecule kinase inhibitors.

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Identification of a kinase profile that predicts chromosome damage induced by small molecule kinase inhibitors.

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