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Bioinformatic approaches to drug repositioning

University of British Columbia

Repositioning existing drugs for new therapeutic uses is an efficient approach to drug discovery. However, most successful repositioning cases to date have been serendipitous; the goal of my thesis was to use computational methods to rationally discover drug repositioning candidates. I first virtually screened (VS) 4621 drugs against 252 drug targets with molecular docking. This method emphasized removing potential false positives using stringent criteria from known interaction docking, consensus scores, and rank information. Published literature indicated experimental evidence for 31 top predicted interactions, supporting the approach. The chemotherapeutic nilotinib was validated as a potent MAPK14 inhibitor in vitro (IC50 40nM), suggesting a potential use in inflammatory diseases. I then applied this method to the cancer target EGFR, predicting the anti-HIV drug tenofovir disoproxil fumarate (TDF) as a novel inhibitor. In vitro, TDF inhibited the proliferation and EGFR-signaling of an EGFR-overexpressing cell line, but did not inhibit EGFR in direct kinase binding assays. This study highlighted limitations of computational and experimental methodologies that should be considered when interpreting or designing other studies. We then screened 1,120 off-patent drugs against the triple-negative breast cancer (TNBC) target p90RSK using both VS and high-throughput (HTS) methods. VS predicted a set of compounds 26-times enriched for known RSK inhibitors and 11 times enriched for HTS hits, underscoring its efficiency. In secondary screens, the chemotherapeutic ellipticine and the bioflavonoids luteolin and apigenin inhibited RSK activity (IC50 0.50-4.77μM), blocked RSK signaling, and inhibited TNBC cell proliferation. These drugs thus have potential to be repositioned to TNBC. Finally, we rationally repositioned renal cell carcinoma drugs for a patient with a rare tongue adenocarcinoma. Whole genome and transcriptome sequencing of the patient’s tumor and normal cells detected sequence, copy number, and expression aberrations, and analysis suggested that the tumor was driven by the RET oncogene. Treatment with RET-inhibiting drugs stabilized the disease for eight months, after which the disease progressed. We also sequenced the post-treatment tumor and found changes consistent with acquired therapeutic resistance. Overall, this thesis details two novel high-throughput approaches for drug repositioning: virtual screening of drugs and targets and personalized medicine via sequencing.

Text

2012-07-31

Attribution-NonCommercial-NoDerivs 3.0 Unported

http://hdl.handle.net/2429/39934

Bioinformatics

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/3.0/