M. Singh, et al.
Bioorganic&MedicinalChemistry28(2020)115547
Fig. 11. Images of vehicle-treated cells and cells
treated with compounds 1, 4, and 27. Differences in
cell morphology are apparent even to a human eye.
Composite image of all wavelengths is shown (blue:
nucleus, green: ER, yellow: nucleoli, orange: Golgi
and plasma membrane, red: mitochondria). (For
interpretation of the references to colour in this
figure legend, the reader is referred to the web
version of this article.)
structural “red flags” associated with their structures (Supporting
Information: Cheminformatics). Importantly, the corresponding dia-
stereomers (compounds 14 and 17) are not active in this experiment,
strengthening the case for a specific interaction that produces the ac-
tivity. Based on the similarity of their fingerprints, compound 1 clusters
with fenbendazole and rotenone, whereas compounds 4, 27, and phe-
nylpyrroline all cluster together in a distinct clade (Fig. 10).
identification of starting points for the discovery of novel bioactive
substances. Creative output of synthetic chemistry coupled with rapid
insights that can be obtained from imaging cell populations treated
with newly-synthesized compounds is a fertile ground for discovery of
bioactive substances with novel mechanisms of action. Widespread
adoption of this bioactivity assessment approach will benefit from a
more standardized set of measured features. Unambiguous naming
conventions would facilitate comparisons between fingerprints gener-
ated at different labs and originating from different experiments.
Additionally, ascribing biological meaning to the observed changes
would provide a more satisfying aspect to this biological annotation
experiment. Connecting the compound structural features to the ob-
served biological fingerprints has the potential to expedite structure–-
activity relationship studies and the identification of novel bioactive
compounds.
A qualitative interpretation of images of cells treated with com-
pounds 1, 4, and 27 reveals drastic changes compared to vehicle
treatment (Fig. 11). Each treatment was hallmarked by an increase in
both mitochondrial and endoplasmic reticulum staining compared to
that of vehicle-treated cells. Cytoplasmic swelling was commonly ob-
served and severe membrane blebbing was abundant. This may indicate
loss of the ability to control intracellular osmotic pressure. Nuclear
fragmentation was clear and frequent. Furthermore, apoptotic bodies
were numerous in the extracellular space for all the compounds that
show increased toxicity. (See Supporting Information for complete data
on toxicity of all control and test compounds.) Vehicle-treated cells are
characterized by well-defined nuclei dotted with numerous nucleoli.
Mitochondrial and ER stain intensities are balanced with that of cyto-
plasm stain. Cellular shape is defined by polygonal borders typical of U-
2 OS cancer line. Imine-containing compound 27 (at 33 μM) produces a
very strong ER and mitochondrial staining, and cells and nuclei are
swollen. Compound 1 at 100 μM causes similar amplification of the
mitochondrial staining. Membrane blebbing advanced with nuclear
fragmentation, and misshapen cells are abundant with a few apoptotic
bodies observed. Effects of compound 4 at 100 μM are similar to those
of compound 1 with abnormally shaped cells, strong ER staining, and
disappearance of numerous nucleoli present in normal U-2 OS cells.
One of the obstacles to the wider adoption of “cell painting” (vide
supra) concerns the uncertainty with respect to the granularity of these
fingerprints, i.e. what are the mechanisms that this technique can re-
liably distinguish? It seems apparent from the accumulated experience
in this area that the compounds that target cytoskeleton will un-
surprisingly produce the strongest fingerprints. In this study, we also
observed that cytotoxic compounds seem to have strong fingerprints
(they are obviously bioactive) and these fingerprints do not all seem to
coalesce around common morphological changes. For instance, the
imines (phenylpyrroline and compound 27) were cytotoxic, but this
cytotoxicity produced a fingeprint different from the cytotoxicity of
vincristine or taxol (Fig. 10). The mechanism of action of compounds 1
and 4 is difficult to precisely assign at this point, and is a topic of on-
going work in our laboratory. As a first step in this process, computa-
tional protein target prediction algorithm27 suggested acetylcholine
esterase and β-secretase as potential protein targets of these com-
pounds.
Annotating the biological-assays-naïve compound collection with
“cell painting” has provided us with the immediate experimental in-
sights into the bioactivities of its members. We will use these insights to
guide the improvements in synthetic chemistry to prepare the collec-
tion, and to define the exact mode of action of the active compounds.
5. Data statement
Raw images and Cell Profiler extracted features per-object are
available upon request. Processed per-well files, analysis scripts, code to
generate images, and compound.sdf files with annotated NMR shifts are
available on the laboratory’s GitHub repository associated with this
Declaration of Competing Interest
None.
Acknowledgments
We thank the University of Kansas New Faculty General Research
Fund, General Research Fund, and Protein Structure–Function COBRE
for financially supporting this project. We acknowledge Dr. Victor Day
for X-ray diffraction experiments, and the NSF-MRI grant CHE-0923449
that was used to purchase the X-ray diffractometer and software used in
this study. We thank Ms. Ankita Ramprasad, Ms. Annu Anna Thomas,
and Mr. Matthew McCurry for their help with reproducing previously
reported syntheses. We thank KU’s NMR core facilities for acquiring
characterization data that made conclusions of this publication
stronger. We are grateful to Prof. Robert Hanzlik for improving the
quality of the manuscript, and to Prof. Patrick S. Mariano (University of
New Mexico) for the helpful e-mail exchange regarding the structure of
compound 27.
4. Conclusions
We have described a synthetic chemistry strategy to prepare a col-
lection of 27 molecules occupying new chemical space, and we gener-
ated their bioactivity fingerprints through “cell painting.” From these
measurements we identified two compounds that could be classified as
bioactive. This project demonstrated the feasibility of experimental
Appendix A. Supplementary material
Supplementary data associated with this article can be found, in the
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