Yeongju Lee’s research while affiliated with The Scripps Research Institute and other places

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Publications (1)


Library-versus-library screening defines new RNA-binding small molecules and druggable targets
a, 2DCS analysis of more than 61 million theoretical interactions, identifying new interactions between small molecules and RNA motifs. b, The newly identified small-molecule RNA binders (n = 344) included 156 different scaffolds that fall into 79 major classes based on scaffold similarities. Among the top 10 most abundant classes (collectively covering 59.6% of all hits), six are new classes (green). c, Motif distribution from a 3 × 3 randomized RNA library used for 2DCS screening. As expected, 3 × 3 and 2 × 2 internal loops comprise the majority (85.4% total) of the library. Motifs that bound to C1–C6 showed a significant enrichment for 3 × 3 internal loops (P < 0.001) and one-nucleotide bulges (P < 0.001). A total of 1,044 motifs bound to C1–C20 with Zobs > 8. Preference for 3 × 3 internal loops and one-nucleotide bulges was collectively observed for these compounds. Of these 1,044 motifs, only 23 (2.2%) are present in highly expressed human transcripts (n = 2,712 total motifs), and 375 are new motifs with no previously known small-molecule binder. Inforna contains over 100,000 RNA–small molecule interactions and 6,453 unique RNA motifs of various types. d, Although around 6% of all miRNAs can be bound by C1–C6, only about 30% of targetable sites within them are functional (Drosha or Dicer processing site) and are therefore predicted to induce a biological effect. The other approximately 70% are unproductive interactions that are predicted to be biologically silent. We identified that 48% of miRNAs that have ligandable non-functional sites are potential substrates for RNase L, which could be targeted by RIBOTACs. Thus, biologically inert binders can be converted into bioactive RIBOTACs that provoke targeted degradation. Statistical significance referred to in c was calculated using two-tailed Student’s t-tests.
Pre-miR-155-RIBOTAC selectively degrades pre-miR-155 in an RNase-L-dependent manner in breast cancer cells
a, Schematic of converting an inert binder engaging pre-miR-155 into an active RIBOTAC degrader. b, Structures of the compounds used to target pre-miR-155. c, The effects of pre-miR-155-RIBOTAC on mature (mat) (n = 4 biological replicates), pre- (n = 3 biological replicates) and pri- (n = 3 biological replicates) miR-155 levels, competed by increasing concentrations of pre-miR-155-binder in MDA-MB-231 cells. d, The effect of siRNA knockdown of RNase L on pre-miR-155-RIBOTAC-mediated cleavage of pre-miR-155 in MDA-MB-231 cells, as determined using RT–qPCR. n = 3 biological replicates. e, Immunoprecipitation of pre-miR-155 using an anti-RNase L antibody in the presence of pre-miR-155-RIBOTAC in MDA-MB-231 cells (n = 3 biological replicates). f, The effect of pre-miR-155-amide-binder (left; 100 nM; n = 4 biological replicates) and pre-miR-155-RIBOTAC (right; 100 nM; n = 3 biological replicates) on the levels of the 373 miRNAs expressed in MDA-MB-231 cells. FC, fold change. g, Western blot analysis of SOCS1, a direct target of miR-155, after treatment of MDA-MB-231 cells with pre-miR-155-RIBOTAC (n = 3 biological replicates). h, The effect of pre-miR-155-RIBOTAC on the activity of a SOCS1 3′ UTR-luciferase reporter transfected into HEK293T cells, establishing both dose (left) and time dependence (right; n = 4 biological replicates). Data are mean ± s.d. (c–e, g and h). Statistical significance was determined using two-tailed Student’s t-tests (c–e, g and h) or a Wald’s test (f).
Source data
Pre-miR-155-RIBOTAC selectively degrades pre-miR-155 and reduces lung colonization in vivo
a, Left, proteome-wide changes in MDA-MB-231 cells treated with pre-miR-155-RIBOTAC (100 nM) versus vehicle (n = 3 biological replicates). Right, pre-miR-155-RIBOTAC significantly upregulated miR-155 related proteins (n = 98 proteins), as indicated by a Kolmogorov–Smirnov analysis (right) of their levels versus all proteins (n = 3 biological replicates). b, The effect of pre-miR-155-RIBOTAC on MDA-MB-231 cell migration (n = 3 biological replicates); 2 fields of view were quantified per replicate. Scale bars, 0.5 mm. c, pre-miR-155-RIBOTAC suppresses lung colonization in vivo, as determined by counting lung nodules (n = 5 mice) and by haematoxylin and eosin (H&E) staining (n = 5 mice; 2 fields of view were quantified per replicate). Scale bars, 1 mm (left) and 0.2 mm (right). d, The effect of pre-miR-155-amide-binder and pre-miR-155-RIBOTAC on pre-miR-155 levels in vivo, as determined by RT–qPCR using primers selective for human pre-miR-155 (n = 3 mice). Data are mean ± s.d. (b and d). Statistical significance was determined using a Wald’s test (a) or two-tailed Student’s t-tests (b–d).
Source data
JUN-RIBOTAC impairs pancreatic tumour cell proliferation and migration by selectively degrading JUN mRNA
a, Schematic of JUN degradation by targeting the JUN IRES. b, The structures of compounds used to target JUN mRNA. c, The effect of JUN-RIBOTAC and JUN-binder on JUN mRNA levels in MIA PaCa-2 cells after treatment for 72 h, as determined using RT–qPCR (n = 6 biological replicates). d, The effect of JUN-RIBOTAC on JUN protein levels in MIA PaCa-2 cells (n = 4 biological replicates). e, The effect of JUN-RIBOTAC on JUN mRNA levels in MIA PaCa-2 cells in which RNase L was knocked down by CRISPR (n = 3 biological replicates) and in the corresponding MIA PaCa-2 control cell line in which CRISPR editing was performed using a scrambled guide RNA (n = 4 biological replicates), as determined using RT–qPCR. f, The effect of JUN-RIBOTAC on the proliferation of MIA PaCa-2 cells (n = 6 biological replicates). g, The effect of JUN-RIBOTAC on the invasiveness of MIA PaCa-2 cells, as determined using a Boyden chamber assay (n = 2 biological replicates; 2 fields of view were quantified per replicate). Data are mean ± s.d. (c–f). Statistical significance was determined using two-tailed Student’s t-tests (d–f) and one-way analysis of variance (ANOVA) adjusted for multiple comparisons (c).
Source data
MYC-RIBOTAC selectively targets MYC in an RNase-L-dependent manner
a, Schematic of the targeted degradation of the MYC IRES. b, Compound structures. c, The effect of MYC-binder and MYC-RIBOTAC on MYC mRNA levels in HeLa cells, as determined using RT–qPCR. n = 3 biological replicates. d, The effect of MYC-RIBOTAC on MYC protein levels in HeLa cells (n = 3 biological replicates). e, The effect of MYC-RIBOTAC on the proliferation (left) and apoptosis (right) of HeLa cells (n = 3 biological replicates). f, The effect of MYC-RIBOTAC on MYC IRES luciferase reporter in HEK293T cells (left) or on a control reporter lacking the IRES (right)(n = 3 biological replicates). g, Transcriptome-wide changes in HeLa cells treated with MYC-RIBOTAC (10 μM) after treatment for 48 h (n = 3 biological replicates). EGR1 is a well-known downstream target of MYC⁵⁰. h, Cumulative distribution analysis of the effect of MYC-RIBOTAC and a MYC-selective siRNA on 87 well-validated downstream targets of MYC, or on the downstream targets of HIF-1α, as indicated by a Kolmogorov–Smirnov analysis of their levels relative to all proteins (n = 3 biological replicates). i, The effect of MYC-Ctr and MYC-RIBOTAC on MYC mRNA levels in Namalwa Burkitt lymphoma cells (n = 3 biological replicates) compared with the vehicle (n = 6 biological replicates). j, The effect of MYC-RIBOTAC on MYC protein levels in Namalwa cells (n = 2 biological replicates). k, The effect of MYC-RIBOTAC on the cell cycle of Namalwa cells. n = 2 biological replicates. l, The ability of MYC-RIBOTAC or MYC-Ctr to induce apoptosis of Namalwa cells (n = 2 biological replicates). m, The effect of MYC-RIBOTAC on colony formation of Namalwa cells (n = 2 biological replicates). Data are mean ± s.d. (c–f and i). Statistical significance was determined using a one-way ANOVA adjusted for multiple comparisons (c), two-tailed Student’s t-tests (d–i), Wald’s test (g), or Kolmogorov–Smirnov test (h).
Source data
Programming inactive RNA-binding small molecules into bioactive degraders
  • Article
  • Full-text available

May 2023

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626 Reads

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92 Citations

Nature

Yuquan Tong

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Yeongju Lee

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Xiaohui Liu

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Target occupancy is often insufficient to elicit biological activity, particularly for RNA, compounded by the longstanding challenges surrounding the molecular recognition of RNA structures by small molecules. Here we studied molecular recognition patterns between a natural-product-inspired small-molecule collection and three-dimensionally folded RNA structures. Mapping these interaction landscapes across the human transcriptome defined structure–activity relationships. Although RNA-binding compounds that bind to functional sites were expected to elicit a biological response, most identified interactions were predicted to be biologically inert as they bind elsewhere. We reasoned that, for such cases, an alternative strategy to modulate RNA biology is to cleave the target through a ribonuclease-targeting chimera, where an RNA-binding molecule is appended to a heterocycle that binds to and locally activates RNase L¹. Overlay of the substrate specificity for RNase L with the binding landscape of small molecules revealed many favourable candidate binders that might be bioactive when converted into degraders. We provide a proof of concept, designing selective degraders for the precursor to the disease-associated microRNA-155 (pre-miR-155), JUN mRNA and MYC mRNA. Thus, small-molecule RNA-targeted degradation can be leveraged to convert strong, yet inactive, binding interactions into potent and specific modulators of RNA function.

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Citations (1)


... Thus, positional reactivity could be a general strategy for improving the selectivity of binding small molecules, as observed for targeted degradation approaches, either directly 100 or via enzymatic recruitment. 101 was not certified by peer review) is the author/funder. All rights reserved. ...

Reference:

Discovery of RNA-Reactive Small Molecules Guides Design of Electrophilic Modules for RNA-Specific Covalent Binders
Programming inactive RNA-binding small molecules into bioactive degraders

Nature