Two-dimensional combinatorial screening enables the bottom-up design of a microRNA-10b inhibitor

Article abstract of DOI:10.1039/c3cc00173c

The RNA motifs that bind guanidinylated kanamycin A (G Kan A) and guanidinylated neomycin B (G Neo B) were identified via two-dimensional combinatorial screening (2DCS). The results of these studies enabled the bottom-up design of a small molecule inhibitor of oncogenic microRNA-10b. The Royal Society of Chemistry.

Full text of DOI:10.1039/c3cc00173c

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Two-dimensional combinatorial screening enables
the bottom-up design of a microRNA-10b
inhibitor†
Cite this: Chem. Commun., 2014,
50, 3027
Received 8th January 2013,
Accepted 19th December 2013
Sai Pradeep Velagapudiab and Matthew D. Disney*a
DOI: 10.1039/c3cc00173c
www.rsc.org/chemcomm
The RNA motifs that bind guanidinylated kanamycin A (G Kan A) and
guanidinylated neomycin B (G Neo B) were identified via two-
dimensional combinatorial screening (2DCS). The results of these
studies enabled the ‘‘bottom-up’’ design of a small molecule inhibitor
of oncogenic microRNA-10b.
RNA drug targets in the human transcriptome are numerous,
however most drugs elicit their effects by modulating protein, not
RNA, function.1–3 This is perhaps due to a lack of fundamental
understanding about RNA–ligand interactions, particularly the RNA
secondary structural elements (motifs) that are targetable and small
molecules that are biased for binding RNA motifs. Two-dimensional
combinatorial screening (2DCS) has been used to identify the
privileged RNA motifs that bind small molecules via selection.4
Two of the most significant concerns for small molecules that target
RNA are cell permeability and specificity. Fortuitously, many mole-
cular transporters bind RNA, notably guanidinylated aminoglyco-
sides.5 Herein, we report the identification of the preferred RNA
internal loops that bind two guanidinylated aminoglycosides and
Fig. 1 Secondary structures of the nucleic acids and small molecules
used in this study. (left) 1 is the secondary structure of the 4096-member
RNA 3 ꢀ 3 nucleotide internal loop library; 2–5 are the competitor RNAs
used to constrain 2DCS selections to the randomized region in 1. Oligo-
nucleotides 7 and 8 are DNA competitors, and 9 is the cassette into which the
randomized region was inserted. (right) Structures of azide-functionalized
guanidinylated derivatives of kanamycin A and neomycin B.
the development of a bioactive compound targeting a precursor transferred to the slide surface to afford a dose response after
microRNA (miRNA) by using those preferences.
hybridization with 32P-labelled RNA library 1 (Fig. S-10, ESI†).
In 2DCS, a small molecule microarray is hybridized with an RNA Hybridization is completed in the presence of unlabeled com-
library of a discrete secondary structural element such as an internal petitor oligonucleotides 2–8 (Fig. 1) to constrain selected inter-
loop (1, for example; Fig. 1). The RNAs bound to each small molecule actions to the randomized regions in 1.4 RNAs bound at the
are excised from the array, amplified, and sequenced. Thus, this lowest loading above the background were harvested, amplified,
approach identifies the privileged RNA motifs for binding a small and sequenced (Tables S-1 and S-2, ESI†), as interactions captured
molecule from thousands of combinations. To enable 2DCS studies at lower ligand loading have the highest affinity.4
of guanidinylated aminoglycosides, G Neo B and G Kan A derivatives
The members of 1 selected for both small molecules were
(Fig. 1) were synthesized that contain an azide handle for site-specific analysed to define features that impart binding affinity using
immobilization onto alkyne-functionalized agarose microarrays the RNA Privileged Space Predictor program, RNA-PSP, (v 2.0).7
(Fig. S-1–S-9, ESI†).6 Serial dilutions of the compounds were RNA-PSP compares features in 1 (such as a GC step) to the features
in selected motifs. A Z-score (which can be converted to the
corresponding two-tailed p-value) is computed, which is a measure
of statistical confidence that a feature in a selected motif is truly
‘‘privileged’’ for binding to the small molecule (Fig. S-11, ESI†).
A selected RNA motif contains multiple statistically significant
a Department of Chemistry, The Scripps Research Institute, Scripps Florida,
130 Scripps Way #3A1, Jupiter, Florida 33458, USA. E-mail: Disney@scripps.edu
b Department of Chemistry, The State University of New York at Buffalo, Buffalo,
New York 14260, USA
features. Previous studies have shown that RNAs with more
statistically significant features that contribute positively to
† Electronic supplementary information (ESI) available: Synthetic methods and
additional data. See DOI: 10.1039/c3cc00173c
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molecular recognition have a higher affinity.7,8 In fact, affinity
Sum Z-scores can also be used to predict selectivity.11 The
scales with the sum of the Z-scores for each statistically significant affinities of two RNAs selected to bind G Neo B and two RNAs
feature, or Sum Z-score. The range of Sum Z-scores for G Neo B selected to bind G Kan A were measured for binding both small
and G Kan A are shown in Fig. S-11 (ESI†). As expected, RNA molecules (labelled in Fig. S-11, ESI†). The RNAs were chosen based
motifs selected to bind have the highest Sum Z-scores. Motifs on their Sum Z-scores; loops with large Sum Z-scores for their
selected to bind G Neo B have low Sum Z-scores for G Kan A and cognate ligand and small Sum Z-scores for the non-cognate ligand
vice versa, indicating that they are specific for the aminoglycoside were selected. As expected, this analysis allowed for prediction of
they were selected to bind (Fig. S-11 and S-12, ESI†).
compound selectivity. For example, no saturation was observed
The secondary structures of selected sequences with the when up to 10 mM RNA G Neo B IL 8 was added to 50 nM G Kan A
highest Sum Z-scores were analysed,9 and their affinities deter- (Fig. 2 and Fig. S-18, ESI†). Likewise, the Kd for RNA motif G Neo B
mined (Fig. 2). The affinities of RNAs selected for G Neo B range IL 5 and G Kan A is 1400 nM (approximately 5-fold selective for
from E100 to 550 nM while affinities for RNAs selected for G Neo B) (Fig. 2 and Fig. S-18, ESI†). The observation that G Neo B IL5
G Kan A range from E200 to 650 nM (Fig. 2A and B; Fig. S-13 exhibits a lower selectivity is expected as the Sum Z-score for Kan A is
and S-14, ESI†). Importantly, both compounds bind weakly to higher than that for G Neo B IL 8 (Fig. S-11, ESI†). The selectivity of
the entire library 1 and the cassette 9 into which the randomized RNA motifs selected to bind G Kan A was measured for binding G Neo
region was embedded (Fig. 1 and Fig. S-16, ESI†). Six members of 1 B. No saturation is observed when up to 10 mM G Kan A IL 1 or G Kan
were randomly chosen that have low Sum Z-scores for both com- A IL 2 is added to 50 nM G Neo B (Fig. 2 and Fig. S-18, ESI†).
pounds (bottom 10%) and their affinities measured. As expected, Collectively, these studies illustrate that higher and lower Sum
none of these RNA motifs (NS IL 1–NS IL 6) bind G Neo B or G Kan A Z-scores indicate tight and weak binding, respectively, and can be
(Fig. 2C and Fig. S-16, ESI†). Thus, high and low Sum Z-scores used to predict ligand selectivity, also highlighting that interactions
can accurately predict the affinity of RNA motif–ligand inter- identified by 2DCS are selective.
actions. The effect of the cassette into which an RNA motif is
Traditional drug or chemical probe discovery is accomplished
embedded on affinity was also investigated. As expected from by screening of small molecules for modulating a specific target.
previous studies, little difference in affinity is observed when By using the information obtained via 2DCS herein, a different
the stem is altered (Fig. 1 and Fig. S-17, ESI†).4,10
‘‘bottom-up’’ route was implemented. In this approach, RNA motif–
small molecule interactions identified by 2DCS were mined against
the RNA folds in the human transcriptome, namely miRNA pre-
cursors. MiRNAs function by binding to the 30 untranslated regions
(UTRs) of mRNAs, negatively regulating translation. MiRNAs
are transcribed as primary (pri-) miRNAs that are processed in
the nucleus by Drosha, and then exported to the cytoplasm as
pre-miRNAs that are processed by Dicer to form the mature
miRNA (Fig. 3A).12 Many miRNAs cause or contribute to various
diseases.13 Binding of a small molecule to Drosha or Dicer
processing sites could inhibit biogenesis of aberrantly expressed
miRNAs, thereby alleviating disease.
By mining the RNA motif–small molecule pairs identified
herein against the secondary structures of miRNA precursors in
miRBase,14 we identified that G Neo B IL 12 is the Drosha processing
site in the miR-10b precursor. Overexpression of miR-10b has been
implicated in numerous cancers with invasive and metastatic
characteristics,15 and there are no known small molecule effectors
of miR-10b. Inhibition of miR-10b biogenesis could increase
the production of downstream proteins that it regulates. We
validated that G Neo B binds the internal loop in miR-10b,
including its non-nearest neighbour closing pairs, by embedding
50AUACC/30UAAGG in 9 and measuring the affinity, affording a
Kd of 417ꢁ 60 nM (Fig. S-19, ESI†).
Next, we studied the effect of G Neo B on miR-10b biogenesis.
HeLa cells were transfected with a construct that allows over-
production of pri-miR-10b and then treated with G Neo B. As
shown in Fig. 3B, G Neo B inhibits production of mature miR-10b
by 50% at a dosage of 100 mM. Importantly, G Neo B does not
affect biogenesis of a control miRNA that is not predicted to
bind the small molecule (miR-149) as determined by a two-
tailed student t-test (Fig. 3B and Fig. S-20, ESI†).16 A decrease in
Fig. 2 Secondary structures of the internal loops that were studied for binding
ligands in this study. The nomenclature for each loop is an abbreviated ligand
name (G Kan A or G Neo B) followed by IL (refers to internal loop) and a
unique number. The dissociation constant is reported in nM below the loop
identifier. (A) The internal loops selected to bind G Neo B. (B) The internal
loops selected to bind G Kan A. (C) Loops that were not selected to bind
either ligand. As predicted, these loops bind weakly to both G Kan A and
G Neo B with Kds 4 1000 nM.
3028 | Chem. Commun., 2014, 50, 3027--3029
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and miR-122 production by targeting transcription factors.20,21
Although G Neo B has modest activity, it can be optimized. For
example, modular assembly is a robust approach that improves the
bioactivity of small molecules that target repeating transcripts.22–24
The azide handle of G Neo B makes it amendable to such an
approach. Although modular assembly increases molecular weight,
which is generally considered unfavourable, it is possible that this
potential issue could be assuaged because G Neo B is a molecular
transporter. Importantly, these studies highlight that small mole-
cules can be designed to target RNA by using the output of 2DCS,
rather than using high throughput screening.
We thank Matthew Belair and Pavel Tsitovich for studies
on the synthesis of G Neo B. This work was funded by the
National Institutes of Health (R01-GM097455). MDD is a
Research Corporation Cottrell Scholar and a recipient of the
Camille & Henry Dreyfus Teacher-Scholar Award.
Fig. 3 G Neo B inhibits miR-10b biogenesis and boosts production of a
downstream target. (A) miR-10b is processed to produce the mature
miRNA in two steps, first by Drosha in the nucleus and then by Dicer in
the cytoplasm. The mature miRNA modulates protein expression. The
target site for G Neo B is highlighted by a purple circle. (B) G Neo B inhibits
production of mature miR-10b as determined by qRT-PCR. (C) G Neo B
increases the amount of pri-miR-10b and diminishes pre- and mature
miR-10b levels, as expected if G Neo B binds to the Drosha site and inhibits
processing. (D) G Neo B affects production of luciferase when a luciferase
mRNA is under the control of miR-10b, validating that G Neo B affects
miRNA biogenesis and downstream protein targets (*p o 0.05; **p o 0.01
as determined by a two-tailed student t-test; n Z 3).
References
1 J. R. Thomas and P. J. Hergenrother, Chem. Rev., 2008, 108, 1171–1224.
2 C. S. Chow and F. M. Bogdan, Chem. Rev., 1997, 97, 1489–1514.
3 L. Guan and M. D. Disney, ACS Chem. Biol., 2012, 7, 73–86.
4 J. L. Childs-Disney, M. Wu, A. Pushechnikov, O. Aminova and
M. D. Disney, ACS Chem. Biol., 2007, 2, 745–754.
5 N. W. Luedtke, P. Carmichael and Y. Tor, J. Am. Chem. Soc., 2003,
125, 12374–12375.
6 T. R. Chan, R. Hilgraf, K. B. Sharpless and V. V. Fokin, Org. Lett.,
2004, 6, 2853–2855.
7 S. P. Velagapudi, S. J. Seedhouse and M. D. Disney, Angew. Chem.,
Int. Ed., 2010, 49, 3816–3818.
8 S. P. Velagapudi, S. J. Seedhouse, J. French and M. D. Disney, J. Am.
Chem. Soc., 2011, 133, 10111–10118.
9 D. H. Mathews, M. D. Disney, J. L. Childs, S. J. Schroeder, M. Zuker
and D. H. Turner, Proc. Natl. Acad. Sci. U. S. A., 2004, 101, 7287–7292.
mature miRNA levels could occur through various mechanisms.
G Neo B was designed to bind the Drosha processing site of miR-10b,
thereby inhibiting processing. If G Neo B inhibits Drosha processing,
then there should be a boost in the amount of pri-miR-10b and 10 M. D. Disney, L. P. Labuda, D. J. Paul, S. G. Poplawski,
A. Pushechnikov, T. Tran, S. P. Velagapudi, M. Wu and
concomitant decreases in the amount of pre- and mature forms. We
J. L. Childs-Disney, J. Am. Chem. Soc., 2008, 130, 11185–11194.
therefore determined the expression levels of pri-, pre-, and mature
11 S. P. Velagapudi, A. Pushechnikov, L. P. Labuda, J. M. French and
miR-10b by qRT-PCR (Fig. 3C and Fig. S-21, ESI†). As expected,
G Neo B increases the amount of pri-miRNA by B60% and
decreases the pre- and mature forms by B30% and B60%,
respectively (Fig. 3C and Fig. S-21, ESI†).
Next, we determined if G Neo B can remove repression of down-
stream targets of miR-10b using a model system. MiR-10b directly
M. D. Disney, ACS Chem. Biol., 2012, 7, 1902–1909.
12 D. P. Bartel, Cell, 2004, 116, 281–297.
13 G. A. Calin and C. M. Croce, Oncogene, 2006, 25, 6202–6210.
14 S. Griffiths-Jones, H. K. Saini, S. van Dongen and A. J. Enright,
Nucleic Acids Res., 2008, 36, D154–D158.
15 L. Ma, F. Reinhardt, E. Pan, J. Soutschek, B. Bhat, E. G. Marcusson,
J. Teruya-Feldstein, G. W. Bell and R. A. Weinberg, Nat. Biotechnol.,
2010, 28, 341–347.
suppresses HomeoboxD10 (HOXD10) mRNA, which functions as a 16 L. Jin, W. L. Hu, C. C. Jiang, J. X. Wang, C. C. Han, P. Chu,
tumor suppressor17 by inhibiting genes involved in cell migration
L. J. Zhang, R. F. Thorne, J. Wilmott, R. A. Scolyer, P. Hersey,
X. D. Zhang and M. Wu, Proc. Natl. Acad. Sci. U. S. A., 2011, 108,
and extracellular matrix remodelling such as RhoC, a3-integrin and
15840–15845.
Mt1-MMP.18 The HOXD10 30 UTR was fused to luciferase; therefore, 17 M. Carrio, G. Arderiu, C. Myers and N. J. Boudreau, Cancer Res.,
2005, 65, 7177–7185.
18 L. Ma, J. Teruya-Feldstein and R. A. Weinberg, Nature, 2007, 449,
luciferase activity is inversely proportional to mature miR-10b levels.
The construct was co-transfected with the plasmid encoding pri-miR-
682–688.
10b into HeLa cells followed by treatment with G Neo B. In agreement 19 D. Bose, G. Jayaraj, H. Suryawanshi, P. Agarwala, S. K. Pore,
R. Banerjee and S. Maiti, Angew. Chem., Int. Ed., 2012, 51, 1019–1023.
20 K. Gumireddy, D. D. Young, X. Xiong, J. B. Hogenesch, Q. Huang
with the decrease in mature miR-10b observed by qRT-PCR (Fig. 3A
and B), G Neo B stimulates production of luciferase by 1.5-fold
and A. Deiters, Angew. Chem., Int. Ed., 2008, 47, 7482–7484.
(Fig. 3D). Importantly, G Neo B does not affect luciferase production 21 D. D. Young, C. M. Connelly, C. Grohmann and A. Deiters, J. Am.
Chem. Soc., 2010, 132, 7976–7981.
22 J. L. Childs-Disney, J. Hoskins, S. Rzuczek, C. Thornton and
in the absence of miR-10b, as determined by co-transfection of the
luciferase-HOXD10 construct and a control miRNA plasmid that does
M. D. Disney, ACS Chem. Biol., 2012, 7, 856–862.
not regulate HOXD10 (miR-149) (Fig. 3D).
23 J. L. Childs-Disney, R. Parkesh, M. Nakamori, C. A. Thornton and
M. D. Disney, ACS Chem. Biol., 2012, 7, 1984–1993.
24 A. Pushechnikov, M. M. Lee, J. L. Childs-Disney, K. Sobczak,
J. M. French, C. A. Thornton and M. D. Disney, J. Am. Chem. Soc.,
2009, 131, 9767–9779.
Streptomycin is the only other small molecule known to
affect miRNA biogenesis in cells by directly targeting a miRNA
(miR-21);19 other compounds have been shown to affect miR-21
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