1. The Elements of Translational Chemical Biology
Robert A. Copeland, P. Ann Boriack-Sjodin 
Cell Chemical Biology 
Volume 25, Issue 2, Pages (February 2018)
DOI: /j.chembiol
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2. Figure 1
Idealized Plots Illustrating the Expected Relationships of Translational Chemical Biology
(A) Idealized graph of IC50 for inhibition of intracellular biochemical activity as a function of IC50 for inhibition of cell-free biochemical activity of a target, illustrating the three phases of correlation typically seen in such experiments. This graph reflects the expected behavior for a pharmacophore series of compounds that bind a specific target and thereby elicit modulation of intracellular biochemical signal(s) associated with that target according to Element 1.
(B) Idealized graph of IC50 for phenotypic effect as a function of intracellular biochemical IC50 for modulators of a specific target. This graph reflects the expected behavior for a pharmacophore series of compounds that modulate the intracellular biochemical activity of a specific target and thereby elicit a phenotypic effect according to Element 2.
(C) Idealized graph of differential phenotypic impact of compound exposure for cells representing a specific genotypic alteration relative to cells without the altered genotype. In this example, cells harboring the specific genotypic alteration (e.g., a mutation in a target protein) are much more sensitive to compound exposure, in terms of phenotypic impact, than are their wild-type counterparts. See Element 4 in Box 1.
Cell Chemical Biology  , DOI: ( /j.chembiol )
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3. Figure 2
Experimental Examples of Correlation Plots between Cell-Free Target Binding or Activity Assays, Modulation of Intracellular Target Biochemical Activity, and Phenotypic Effect (Elements 1 and 2)
(A) Relationship between inhibition of kinesin spindle protein enzymatic activity in cell-free assays and antiproliferative activity in cell culture for a series of KSP inhibitors. Data from Parrish et al. (2007).
(B) Relationship between inhibition of AKT kinase activity in cell-free assays and inhibition of intracellular substrate phosphorylation for a series of AKT inhibitors. Note the deviations from linearity at both the high- and low-affinity extremes for this chemical series. Nota bene: here, in contrast to the idealized plot present in Box 1, the deviation from linearity for high-potency compounds is likely due to the limited dynamic range of the cellular assay rather than limitations of the enzymatic assay. Data from Heerding et al. (2008).
(C) Relationship between compound affinity for the Alzheimer's γ-secretase within subcellular membranes and phenotypic output (secretion of Aβ peptide from intact cells) for a series of γ-secretase inhibitors. Data from Seiffert et al. (2000).
(D) Relationship between inhibition of intracellular H3K27 methylation and antiproliferative phenotype for a series of inhibitors of the protein methyltransferase EZH2. Data from Raimondi (2014) and Kuntz et al. (2016).
Cell Chemical Biology  , DOI: ( /j.chembiol )
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4. Figure 3
Experimental Examples of Stratification of Phenotypic Response in Cell Culture for Targeted Compounds Based on a Specific Genotypic Signature
(A) Antiproliferative activity of the B-Raf V600E mutant selective kinase inhibitor PLX3042 in melanoma cells bearing the B-Raf V600E mutation (left) or wild-type B-Raf (right). Data from Yang et al. (2010).
(B) Antiproliferative activity of the EZH2 inhibitor tazemetostat (EPZ-6438) in soft-tissue sarcoma cells that are negative for the protein INI1 (MRT cells; left) or positive (i.e., wild-type) for INI1. Data from Knutson et al. (2013). The error bars represent the SEM for each group.
Cell Chemical Biology  , DOI: ( /j.chembiol )
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