The determination of intracellular accumulation and target selectivity/specificity is an essential and challenging aspect of modern probe development. Although controversial "rules" have been proposed to account for the bioavailability of orally administered drugs, techniques to determine target selectivity and intracellular compartmentalization of drugs within living cells have not been adequately developed. A lead compound identified from high-throughput screening is generally not suitable for in vivo biological use until a systematic evaluation of the small molecule in cells has taken place. This step is required because highthroughput biochemical and cellular assays are not representative of the multiple different physicochemical environments that exist within living organisms. For example, upon exposure to a small molecule, numerous organelles and compartments within the cell can sequester compounds and prevent association with the desired biological target. Correspondingly, the development of small molecule enzyme inhibitors and receptor modulators is often limited by an inability to target specific proteins. Molecular probes derived from biologically active small molecules have the potential to shed light on these issues. However, many efforts to develop optimal molecular probes suffer the following pitfalls: (1) the inability to accurately monitor where biologically active compounds accumulate within cells, (2) the inability to accurately know which biological targets are truly affected upon exposure of cells to small molecules, and (3) the inability to accurately determine the relative selectivity of compounds for multiple protein targets in their native environment. Previous attempts to address these issues have often used linked fluorophores and other labels that can intrinsically promote differential accumulation of the small molecule away from the site of biological relevance. Consequently, a general systematic protocol is needed to efficiently evaluate the intracellular accumulation and target selectivity of molecular probes. To circumvent these bottlenecks, we propose to develop two complementary approaches to identify proteins that bind small molecules. The first approach will utilize fluorescent probes that readily diffuse through cellular membranes, but do not localize in any compartment. These fluorescent probes will then be used in pulsechase experiments to react with protein-bound inhibitors and monitored via confocal microscopy to elucidate the extent of intracellular sequestration of the fluorescent small molecule. In addition, these probes will be utilized to determine target selectivity by modification of a tether to allow covalent attachment to bound proteins within the cell. Immunopurification and subsequent LCMS will be used to isolate the proteins linked to these fluorophores and determine their identity. A second approach for isolating targets will employ a novel yeast 3- hybrid screen to identify proteins encoded by cDNA libraries that activate transcription by binding to chemical inducers of dimerization (CIDs). To accomplish these objectives, we propose the following specific aims: 1. Develop methodology for visualizing and identifying intracellular protein targets using fluorescent molecular probes. We propose to develop optimal cell-permeable fluorophores, multifunctional tethers, approaches for elucidation of localization of probes, and methods for target identification (ID) using pulse-chase affinity labeling and applications of selective antibodies. 2. Develop yeast three-hybrid (Y3H) systems as tools for the identification of protein targets of small molecules. We propose to combine yeast genetic screening with fluorescence-activated cell sorting (FACS), develop methods to facilitate the penetration of small molecules into living yeast cells, and improve the utility of yeast genetic systems for screening of small molecules and target ID. This proposal is innovative because it aims to address some of the most difficult problems associated with delivering probe molecules identified through high-throughput screening to researchers engaged in real-world biomedical science. Two novel approaches are presented that have the potential to identify and ultimately eliminate undesired cellular trafficking issues and properties that could interfere with targeting of a particular probe. By associating this project with a Specialized Chemistry Center, we also intend to develop general tagging techniques that could be employed as needed in collaboration with other MLPCN groups.

National Institute of Health (NIH)
National Human Genome Research Institute (NHGRI)
Specialized Center--Cooperative Agreements (U54)
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Special Emphasis Panel (ZRG1-IFCN-K)
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University of Kansas Lawrence
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Schroeder, Chad E; Yao, Tuanli; Sotsky, Julie et al. (2014) Development of (E)-2-((1,4-dimethylpiperazin-2-ylidene)amino)-5-nitro-N-phenylbenzamide, ML336: Novel 2-amidinophenylbenzamides as potent inhibitors of venezuelan equine encephalitis virus. J Med Chem 57:8608-21
Chou, Tsui-Fen; Bulfer, Stacie L; Weihl, Conrad C et al. (2014) Specific inhibition of p97/VCP ATPase and kinetic analysis demonstrate interaction between D1 and D2 ATPase domains. J Mol Biol 426:2886-99
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Mukherjee, Sourav; Weiner, Warren S; Schroeder, Chad E et al. (2014) Ebselen inhibits hepatitis C virus NS3 helicase binding to nucleic acid and prevents viral replication. ACS Chem Biol 9:2393-403
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Sweeney, Noreena L; Shadrick, William R; Mukherjee, Sourav et al. (2013) Primuline derivatives that mimic RNA to stimulate hepatitis C virus NS3 helicase-catalyzed ATP hydrolysis. J Biol Chem 288:19949-57
Chou, Tsui-Fen; Li, Kelin; Frankowski, Kevin J et al. (2013) Structure-activity relationship study reveals ML240 and ML241 as potent and selective inhibitors of p97 ATPase. ChemMedChem 8:297-312
Coombs, Thomas C; Tanega, Cordelle; Shen, Min et al. (2013) Small-molecule pyrimidine inhibitors of the cdc2-like (Clk) and dual specificity tyrosine phosphorylation-regulated (Dyrk) kinases: development of chemical probe ML315. Bioorg Med Chem Lett 23:3654-61
Zhang, Jintao; Huan, Jun (2013) Predicting drug-induced QT prolongation effects using multi-view learning. IEEE Trans Nanobioscience 12:206-13

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