Data mining the NCI60 to predict generalized cytotoxicity.

Elimination of cytotoxic compounds in the early and later stages of drug discovery can help reduce the costs of research and development. Through the application of principal components analysis (PCA), we were able to data mine and prove that approximately 89% of the total log GI 50 variance is due to the nonspecific cytotoxic nature of substances. Furthermore, PCA led to the identification of groups of structurally unrelated substances showing very specific toxicity profiles, such as a set of 45 substances toxic only to the Leukemia_SR cancer cell line. In an effort to predict nonspecific cytotoxicity on the basis of the mean log GI 50, we created a decision tree using MACCS keys that can correctly classify over 83% of the substances as cytotoxic/noncytotoxic in silico, on the basis of the cutoff of mean log GI 50 = -5.0. Finally, we have established a linear model using least-squares in which nine of the 59 available NCI60 cancer cell lines can be used to predict the mean log GI 50. The model has R (2) = 0.99 and a root-mean-square deviation between the observed and calculated mean log GI 50 (RMSE) = 0.09. Our predictive models can be applied to flag generally cytotoxic molecules in virtual and real chemical libraries, thus saving time and effort.

Chemoinformatic analysis of a supertargeted combinatorial library of styryl molecules.

Styryl dyes are fluorescent, lipophilic cations that have been used as specific labeling probes of mitochondria in living cells. For specific applications such as epifluorescence microscopy or flow cytometry, it is often desirable to synthesize fluorescent derivatives with optimized excitation, emission, and localization properties. Here, we present a chemoinformatic strategy suitable for multiparameter analysis of a combinatorial library of styryl molecules supertargeted to mitochondria. The strategy is based on a simple additive model relating the spectral and subcellular localization characteristics of styryl compounds to the two chemical building blocks that are used to synthesize the molecules. Using a cross-validation approach, the additive model predicts with a high degree of confidence the subcellular localization and spectral properties of the styryl product, from numerical scores that are independently associated with the individual building blocks of the molecule. The fit of the data indicates that more complex, nonadditive interactions between the two building blocks play a minor role in determining the molecule's optical or biological properties. Moreover, the observed additive relationship allows mechanistic inferences to be made regarding the structure-property relationship observed for this particular class of molecules. It points to testable, mechanistic hypotheses about how chemical structure, fluorescence, and localization properties are related.

Development of novel cell-permeable DNA sensitive dyes using combinatorial synthesis and cell-based screening.

A novel cell-permeable DNA fluorescence sensor was developed based on combinatorially-created styryl dyes and cell-based localization screening.

Expulsion of small molecules in vesicles shed by cancer cells: association with gene expression and chemosensitivity profiles.

Anticancer drug resistance results from selective pressure of chemotherapy, together with mutations or epigenetic changes that make cells refractory to treatment. In cancer cells, we report that gene expression associated with vesicle shedding correlates with chemosensitivity profiles. Experiments with doxorubicin and other small molecules confirm drug accumulation and expulsion in shed vesicles. Relative differences in the rate of vesicle shedding correspond with doxorubicin resistance across various cell lines. Moreover, accumulation of drug in membrane domains in which vesicles originate accounts for drug expulsion in shed vesicles. These observations implicate vesicle shedding as a drug efflux mechanism potentially involved in drug resistance.

A rational approach to personalized anticancer therapy: chemoinformatic analysis reveals mechanistic gene-drug associations.

PURPOSE: To predict the response of cells to chemotherapeutic agents based on gene expression profiles, we performed a chemoinformatic study of a set of standard anticancer agents assayed for activity against a panel of 60 human tumor-derived cell lines from the Developmental Therapeutics Program (DTP) at the National Cancer Institute (NCI). METHODS: Mechanistically-relevant gene:drug activity associations were identified in the scientific literature. The correlations between expression levels of drug target genes and the activity of the drugs against the NCI's 60 cell line panel were calculated across and within each tumor tissue type, using published drug activity and gene expression data. RESULTS: Compared to other mechanistically-relevant gene-drug associations, that of triciribine phosphate (TCN-P) and adenosine kinase (ADK) was exceptionally strong--overall and within tumor tissue types-across the 60 cell lines profiled for chemosensitivity (1) and gene expression (2). CONCLUSION: The results suggest ADK expression may be useful for stratifying TCN-P-responsive vs. non-responsive tumors. Based on TCN-P's mechanism of action and the observed TCN-P:ADK association, we contend that catalytic drug activation provides a rational, mechanistic basis for personalizing cancer treatment based on tumor-specific differences in the expression of drug-activating enzymes.

Supertargeted chemistry: identifying relationships between molecular structures and their sub-cellular distribution.

Supertargeted chemistry is the study of how chemical structures localize or direct molecules to specific sub-cellular compartments in living cells. Supertargeting can be used to increase the activity or specificity of an inhibitor against its target, by concentrating the inhibitor in the particular organelle where the target is active. But, unlike structure-activity relationships, structure-localization relationships are not a simple function of compound concentration. Various aspects of mitochondrial physiology, proteomics and pharmacology have made this the organelle of choice for supertargeting studies. While exploration of supertargeting strategies to this and the other organelles has been limited, combinatorial chemical libraries of fluorescent molecules are beginning to illuminate new supertargeting mechanisms at the sub-cellular level. Moreover, predictive approaches that determine the relationship between a molecule's features and sub-cellular localization are being developed in the related field of functional genomics. Applied to the small molecules, such strategies could prove useful for predicting structure-localization relationships amongst large libraries of compounds.

Combinatorial approach to organelle-targeted fluorescent library based on the styryl scaffold.

The first fluorescent styryl dye library with a broad color range was synthesized by combinatorial condensation of various aldehydes and methyl pyridinium compounds, and their applications as organelle specific staining probes were demonstrated.

A novel microtubule destabilizing entity from orthogonal synthesis of triazine library and zebrafish embryo screening.

The first orthogonal combinatorial synthesis of a high-purity triazine library was demonstrated. Novel triazine-based microtubule inhibitors were discovered by an efficient zebrafish embryo screening and in vitro microtubule polymerization assay.