Context-dependent translation inhibition as a cancer therapeutic modality

Domain: chemistry
Published: 2026-02-24
Editorial outcome: major_revision

Abstract
Recent work has demonstrated that some bacterial antibiotics that inhibit protein synthesis by binding the peptidyl transferase center (PTC) of the ribosome act in a context-dependent manner, inhibiting translation elongation only at specific amino acids. However, this phenomenon has yet to be documented for compounds that inhibit the PTC of the human ribosome. Here, we use structure-based design to guide the synthesis of such PTC-binding, context-dependent inhibitors of the human ribosome, termed interdictors. In the PTC, these compounds preferentially interact with nascent protein residues that exhibit complementary physiochemical properties to the moieties of the small molecule, causing structural rearrangements in both the nascent polypeptide chain and ribosomal RNA. Further, the compounds differentially impact ribosome surveillance pathways, including the ribotoxic stress response. Finally, we confirm their anti-tumor activity after oral dosing in a mouse xenograft model of triple-negative breast cancer. Together, our data establish targeting oncogenic dependency factors through context-dependent inhibition of translation as a potential small molecule therapeutic modality for historically difficult to address cancers.

Introduction
Protein synthesis by the ribosome is the target of many natural product inhibitors both in bacteria and eukaryotes. Such inhibitors can impact any of the four key phases of messenger RNA (mRNA) translation by the ribosome: initiation, elongation, termination and recycling1–3. In rapidly dividing cells such as bacteria, yeasts, and those found in cancer, most ribosomes are engaged in the process of elongation, the stepwise reading of the mRNA sequence and incorporation of matching amino acids into the growing nascent protein chain. Correspondingly, the majority of known translation inhibitors target elongation1,2. While several such inhibitors of human translation elongation have been identified and characterized2,4–7, only one has progressed to clinical use (homoharringtonine; HHT)8,9. A major challenge faced by HHT and other similar inhibitors of translation as cancer therapeutics is the potential for toxicity as HHT indiscriminately inhibits formation of the first peptide bond across all mRNAs10,11. One way to alleviate such toxicity and deliver on the promise of the ribosome as a drug target in oncology12 is to develop context-dependent translation inhibitors that reduce synthesis of specific proteins.

The large physiochemical diversity of protein chains formed on the ribosome during elongation make it uniquely suited for selective inhibition. Over the past decade, a combination of improved structural, biochemical, and genomic approaches has revealed that many natural products historically understood to be global inhibitors of elongation have context- or sequence-dependent activity13–16. In bacterial systems, these include macrolide antibiotics that bind in the nascent polypeptide exit tunnel (NPET) and interact with the growing polypeptide chain13–16, as well as molecules that bind in the peptidyl transferase center (PTC) and interact with the most recently incorporated amino acids in the linear nascent polypeptide15,17. In humans, there is only one documented molecule binding to the NPET, PF846, that has been reported to have any sequence preference18, and no known examples that bind to the PTC. While the polypeptide can form secondary structure in the NPET19, the narrow steric constraints of the PTC permit only a strictly linear polypeptide conformation, potentially enabling rational design of molecules that interact with select target peptides with high precision. The human ribosome PTC is therefore an attractive target for structure-based drug design to inhibit the synthesis of select protein targets, especially those that may lack accessible binding pockets or are intrinsically disordered and therefore considered “undruggable” by traditional small molecule approaches20.

One example of a target for which selective inhibition of translation may constitute a powerful therapeutic approach is MYC, which is among the most commonly activated (~70%) genes in human cancers21,22. MYC has very rapid protein and RNA turnover kinetics23,24, and is almost entirely unstructured21. Global translation inhibition by HHT or other natural products has been reported to kill cancer cells directly by reducing the abundance of short-lived oncogenic proteins such as MYC, MCL1, and CCND1, or to sensitize cells to other chemotherapeutic agents25–27. Beyond elongation inhibitors, dysregulated translation control has been extensively targeted in cancer by inhibiting initiation and cap-dependent translation, including targeting the eIF4F complex, mTORC1 signaling, and MNK kinases, all of which preferentially impact oncogenic mRNAs with complex 5´ UTRs and high translational demand, such as MYC, MCL1, and CCND128–30. These studies establish translation control as a validated therapeutic strategy in oncology31,32.

Cancer cell viability can also be impacted through the activation of ribosome surveillance pathways, including the ribotoxic stress response (RSR) leading to apoptosis, as has been documented for the PTC-binding natural product inhibitor anisomycin (ANS)33,34. While this mechanism is not inherently tumor-specific, many cancers may be susceptible to it due to their high translational flux, reliance on short-lived oncogenic proteins, and in some cases, impaired ability to downregulate protein synthesis35–38.

In this work, we therefore set out to develop inhibitors of human translation that bind to the ribosome PTC and inhibit elongation in a context-dependent manner. Leveraging a shared pharmacophore from the natural product ANS as a template, we designed and synthesized small molecules that confer amino-acid sequence selectivity through unique moieties that project toward and engage with the linear polypeptide chain in the PTC. Using ribosome profiling and in vitro biochemistry, we characterize the individual stall-sequence preferences of two such molecules and ANS. As designed, we observe that each analog preferentially interacts with nascent chain peptide residues that have complementary physiochemical properties to the moieties of the small molecule, demonstrating the ability to rationally engineer >15-fold sequence preferences for this modality. Using cryogenic electron microscopy (cryo-EM) of purified human ribosome nascent chain complexes, we confirm the intended interactions between our designed small molecules and the nascent polypeptide chain, and capture rearrangements in the nascent peptide and ribosomal RNA (rRNA) upon interdictor binding. We further characterize these compounds in cells, where we find that interdictors with different sequence preferences can inhibit cancer cell growth but differentially impact the RSR pathway. Finally, after engineering for favorable pharmacokinetic properties we demonstrate anti-tumor efficacy for an interdictor both in cellulo using a panel of MYC-dependent cancer cell lines, and in vivo in the MDA-MB-231 human triple-negative breast cancer (TNBC) xenograft mouse model where we observe 80% tumor growth inhibition after oral dosing. Together our data lay the foundation for context-dependent translation modulation by small molecule drugs as an emerging powerful modality in oncology to target oncogenic proteins that have historically been inaccessible to conventional drug modalities.

Results
Interdictors lead to unique context-dependent translation inhibition in human cells
We leveraged composite pharmacophore descriptors from anisomycin and other known PTC binders to create context-dependent translation inhibitors, which we call interdictors. We applied rational structure-based design principles to maintain the binding interactions of the shared ANS core with the ribosomal RNA39, while attaching substituents to form stabilizing complementary interactions with the amino acids of the nascent peptide chain (Fig. 1a). As a proof of concept, we designed two compounds with clear differentiation in their intended nascent peptide targets. The first compound, IDB-001, includes a basic (S)-2-(pyrrolidin-2-yl)ethan-1-amine (distal pyrrolidine) substituent we predicted would form salt bridges with aspartic and glutamic acid residues in the nascent polypeptide. The second compound, IDB-002, includes a distal non-polar 3-fluorobenzyl substituent we predicted would preferentially interact with hydrophobic side chains of the emerging polypeptide.

To test these hypotheses and investigate the extent of context-dependent inhibition by these molecules and the parent ANS in human cells, we performed ribosome profiling11,40,41 in the MYC-dependent triple-negative breast cancer cell line HCC-1143 treated with either ANS, IDB-001 or IDB-002. We first examined how these molecules globally affected ribosome occupancy across all coding sequences (CDS) in the transcriptome. We found a pronounced accumulation of footprints at the 5´ ends of open reading frames (ORFs), coupled with decreased footprint density near the 3´ ends compared to DMSO-treated controls (Fig. 1b and Supplementary Fig. 1a, b), confirming that compound treatment resulted in a defect in translation elongation40,42–44. Additionally, we observed different levels of ribosome coverage at the start codon itself between the compounds, indicating that these molecules differ in their ability to inhibit the first round of elongation. We next sought to determine whether these global changes in ribosome coverage were uniform across all transcripts or driven by specific mRNAs. To this end, we developed a polarity score for each transcript that reflected the ribosome coverage at each codon, weighted by the position of that codon within the CDS43. This polarity score ranges from −1, indicating that all ribosomes are positioned at the start codon, to +1, indicating that they are entirely clustered at the stop codon. In drug-treated cells, for both interdictors and ANS, polarity scores generally shifted towards negative values, indicating that the majority of transcripts (>95%) exhibited a redistribution of ribosomes towards the 5´ end (Fig. 1c), again consistent with a strong defect in elongation43.

As interdictors are designed to stall translation in a context-dependent manner in the PTC, we next focused on understanding how nascent polypeptide sequence context influenced changes in ribosome occupancy across mRNAs in response to compound treatment. To this end, we identified pause sites where ribosomes accumulated more than expected from the mean transcript coverage in drug-treated cells compared to DMSO controls using a two-tailed Fisher’s exact test45. The nascent polypeptide sequences of significantly enriched pause sites were used to generate sequence logos46 for positions −7 to 0 in the nascent chain (the portion of the nascent polypeptide still engaged in the PTC), where 0 corresponds to the amino acid residue encoded by the codon occupying the P site (Fig. 1d). Notably, in cells treated with ANS, we observed increased ribosome occupancy for footprints containing alanine and serine residues in the −1 polypeptide position (E-site Ala/Ser) (Fig. 1e). In contrast, IDB-001 pause motifs were enriched for acidic residues (Asp/Glu) in the −1 position, in agreement with our design predictions (Fig. 1f). IDB-002 displayed a similar profile to ANS though with a few notable features, including an increased preference for prolines and small hydrophobic residues (Ala, Val, Ile) in the −1 position, and a depletion of large hydrophobic residues (Phe, Tyr) at the same position (Fig. 1g). While we observe some overlap in the pause motifs between compounds, each molecule tested had a substantial number of uniquely targeted positions (Fig. 1h and Supplementary Fig. 1c).

To compare IDB-001 and IDB-002 more directly to ANS and minimize the impact of shared features, we calculated the change in ribosome occupancy across all amino acids in nascent peptides from position −7 to 0 for the compounds relative to ANS (Fig. 1i, j). Unlike the motif analysis, which only focused on the strongest stall sites, this comparison included all ribosome footprints among ORFs which had sufficient coverage (>0.1 read/codon) giving a more complete view of sequence preferences. In the case of IDB-001, this analysis revealed that in addition to the strong acidic signature at position −1, this compound displayed acidic preferences further up the nascent chain (Fig. 1i). Compared to ANS, IDB-001 also shows a minor enrichment of positively charged (Arg, Lys) residues at this position. In absolute terms, both ANS and IDB-001 strongly disfavor these residues, and this apparent enrichment with IDB-001 may reflect its weaker overall inhibition (Supplementary Fig. 1d-f). Notably, this enrichment disappears when IDB-001 is compared to DMSO (Supplementary Fig. 1d-f). When comparing IDB-002 to ANS, we could more readily observe a depletion of ribosome footprints containing bulky side chains (such as Phe, Tyr, Trp) in the −1 position (Fig. 1j). Overall, these findings highlight the sequence preferences of different interdictors, revealing both shared and unique amino acid targeting for each compound.

Interdictors engage nascent polypeptide motifs to elicit context-dependent ribosome stalling
To more deeply characterize the sequence selectivity of each compound, we analyzed pause motifs identified by ribosome profiling across a gradient of drug concentrations (Supplementary Fig. 2). To globally analyze nascent polypeptide motifs enriched by each molecule, we counted the occurrence of every tetrapeptide (amino acids −3 to 0, referred to as 4-mers) in our ribosome footprinting data and performed differential ribosome occupancy analysis47. As anticipated, we found that the number of 4-mers with significantly changing ribosome occupancy decreased with decreasing concentrations of both compounds due to less overall stalling of ribosomes, though the major trends we identified at the highest concentration remained (Fig. 2a, b and Supplementary Fig. 2c-j). By generating sequence logos for all 4-mers with significant enrichment at each concentration, we identified additional sequence features that were not seen in our initial global analysis (Fig. 1f, g). At the lowest drug concentrations (80 nM), we still observe significant tetrapeptide motifs; these may represent the nascent chain sequences where interdictors stall most strongly. In our analysis of these motifs on individual genes, we observe a significant accumulation of ribosomes at these sites, and a depletion of footprints afterward (Supplementary Fig. 3), suggestive of strong elongation stalls. Consistent with these example genes, the global polarity shift in ribosome occupancy became progressively attenuated at lower compound concentrations, paralleling the reduction in significant 4-mers and distinct pause sites (Supplementary Fig. 2a, b).

To determine the biochemical magnitude of this differential stalling, we used an in vitro transcription-translation assay to probe the effect of these compounds on putative stalling or non-stalling peptide motifs. Using our ribosome occupancy data to predict the sensitivity of every 4-mer to IDB-001 and IDB-002, we generated a panel of reporter sequences for testing: two sequences predicted to be strongly inhibited by IDB-001 but not by IDB-002 (FTED & DDEY), two sequences predicted to be strongly inhibited by IDB-002 but not by IDB-001 (FPAK & GAAC), and one sequence that is not strongly preferred by either compound (NTDW). Each reporter contained six repeats of the identified pause motif 4-mer, followed by the 11 amino acid HiBit tag that produces luminescence when released from the ribosome (Fig. 2c and Supplementary Fig. 4a)48,49. Translation of these reporters in vitro, and inhibition by our compounds, could then be followed in real time (Fig. 2d).

We measured the effect of IDB-001 and IDB-002 on the steady-state rate of reporter protein synthesis and calculated IC50 values for each compound by analyzing translation rates versus compound concentration across an 11-point titration (Fig. 2e and Supplementary Fig. 4b). Comparing the IC50 values of each compound on each reporter revealed results in line with the predictions from ribosome profiling (Fig. 2d and Supplementary Fig. 4). We observed 3-fold higher inhibitory activity of IDB-001 than IDB-002 on the FTED reporter, and 6-fold higher on the DDEY reporter (Fig. 2f). Conversely, IDB-002 had a 5-fold stronger inhibitory effect on the FPAK reporter than IDB-001, and 18-fold stronger on the GAAC reporter (Fig. 2f and Supplementary Fig. 4). As predicted, the NTDW reporter was equally inhibited by both compounds (Fig. 2f and Supplementary Fig. 4). When comparing strongly inhibited compound-stall motif pairs and weakly inhibited compound-stall motif pairs for IDB-001, we found that there is at least a 15-fold range of biochemical specificity for nascent peptide sequences (Fig. 2e and Supplementary Fig. 4b, ratio of IC50 for DDEY versus GAAC). Together, these results connect the context-dependence we observe from ribosome profiling with a direct biochemical effect on translation rate, further confirming the context-dependent mechanism of action of these compounds.

Interdictors make sequence-specific interactions with the nascent chain
To better characterize the precise molecular interactions that underlie interdictor function and sequence preference, we used cryo-EM to determine the structure of a compound-bound human ribosome-nascent chain complex (RNC). This complex was stalled on the pause sequence FPAK, which we identified from ribosome profiling and validated biochemically (Fig. 2). To obtain a stalled complex with the peptide sequence FPAK attached to the P-site tRNA, we programmed in vitro transcription-translation with a reporter ending in the FPAK sequence but lacking a stop codon50 (Supplementary Fig. 5). Purified RNCs carrying the FPAK 4-mer were then incubated with IDB-002 before cryo-EM grid preparation.

The resulting reconstructions showed that most tRNA-containing ribosomes were stalled in a classical, post-translocation state with a peptidyl-tRNA bound in the P site (Fig. 3a). The map of the FPAK-containing complex bound to IDB-002 reached a global resolution of 2.2 Å (Table 1, Supplementary Table 1 and Supplementary Fig. 6, 7). In the PTC of the RNC, there is a clear density for IDB-002 in the expected binding site adjacent to the nascent chain, near the narrowest portion of the PTC (Fig. 3a). As intended in our design, modification and addition of functional substituents to the core ANS pharmacophore do not disrupt binding, and IDB-002 retains the stabilizing interactions of ANS with the rRNA (Fig. 3b)39. The core of the compound binds in a pocket formed by 28S rRNA bases including A3905, G3907, C4398, and the phosphate backbone of U4450, G4451, and U4452 (E. coli residues 2059, 2061, 2452, 2504, 2505, 2506 respectively) (Fig. 3b, Supplementary Fig. 7d). In addition, the core pyrrolidine is positioned to hydrogen bond with C4398 (Fig. 3b). The 2-hydroxyl of the core pyrrolidine also hydrogen bonds with U4446 and coordinates a potassium ion (Fig. 3c). Finally, the methoxyphenyl forms π-stacking interactions with C4398 as it extends toward the tRNA (Fig. 3b), all consistent with previous reports2,39.

Density for the nascent chain extends from the P-site tRNA past the small molecule and toward the exit tunnel (Fig. 3d). Assignment of the backbone and side chain positions of the inherently dynamic nascent chain in the exit tunnel was based on both the nascent chain density itself, the density of the tRNA, the mRNA-anticodon site and the sequence of the input mRNA. The non-polar distal fluorophenyl moiety of IDB-002 binds in the pocket formed by FPAK where the side chains of A-1 and P-2 encapsulate the fluorophenyl substituent (Fig. 3d and Supplementary Fig. 8a-c). The A-1 side chain is also positioned to interact with the methoxyphenyl core of IDB-002 (Supplementary Fig. 8b, c). The interactions between the nascent polypeptide chain and the compound result from both steric and electrostatic complementarity of the added distal substituents of IDB-002. Moreover, replacing alanine in the (−1) position of the polypeptide in silico with a bulky residue like tryptophan or phenylalanine is predicted to lead to steric clashes with the compound, suggesting why such residues are depleted from sequences in our ribosome profiling experiments (Fig. 1i, j and Supplementary Fig. 8d-f). Together, this structure supports our targeted structure-based design approach and demonstrates how small-molecule interdictors engage in context-dependent interactions with the nascent protein chain.

Interdictor binding induces structural rearrangements in the polypeptide and rRNA
To demonstrate the ability of these molecules to engage therapeutically relevant targets during their translation, we selected an acidic stretch within the oncogenic transcription factor MYC (D251SEEEQEDE259) that could potentially form strong interactions with IDB-001. Using the same biochemical approach as above, we generated ribosomes stalled on a MYC non-stop mRNA and incubated these with and without IDB-001 before grid preparation (Supplementary Fig. 5).

As above, the majority of ribosomes were stalled with a peptidyl-tRNA in the P site (Supplementary Table 1). The map of the stalled complex without IDB-001 reached a resolution of 2.2 Å, and the stalled complex with IDB-001 reached a resolution of 1.9 Å (Table 1, Supplementary Table 1 and Supplementary Fig. 7e, 9). The identity of the nascent chain in positions 0 to −3 could be modeled in both maps (Fig. 3e, f). Because the two structures differ in the presence of IDB-001, we could directly determine the conformational changes resulting from compound binding. An overlay of the two structures showed that the general backbone of the nascent polypeptide occupied a similar position in the PTC. However, a key difference was a change in the orientation of the aspartic acid at position −1. In the absence of IDB-001, the density for the side chain D-1 was oriented down and away from the compound binding pocket (Fig. 3e). In contrast, in the presence of IDB-001, D-1 was clearly oriented toward the added distal pyrrolidine ring, resulting in a stabilizing salt bridge (Fig. 3f). This suggests that small molecule interdictors can induce small but impactful structural rearrangements within the nascent peptide to form new stabilizing high affinity interactions.

Comparison of these cryo-EM structures with and without bound interdictor also allowed us to determine rRNA conformational changes induced by the compound. Similar to observations with ANS2,39, we find that binding of IDB-001 to the ribosome causes the bases of residues C4398 and U4399 (E.c. 2452 and 2453) to move by approximately 2.7 Å toward the compound to engage in π-stacking interactions, compacting the space in the PTC (Fig. 3g). Moreover, several other bases implicated in the peptidyl transferase reaction change their orientations in the presence of compound. In the absence of compound, U4452 (E. coli 2506), which acts as a gate to control access of the A-site aminoacyl-tRNA to the sensitive P-site tRNA-peptidyl ester bond, alternates between two conformations separated by a 90° swing51–54 (Fig. 3h). In the presence of IDB-001, U4452 instead adopts a position that leaves the gate half closed, potentially affecting peptidyl transfer (Fig. 3h). A3908 (E. coli 2062), which lines the wall of the exit tunnel adjacent to the PTC, has also been shown in previous structures to adopt two distinct conformations that could interact with the growing polypeptide chain, one where the base portion lies flat against the tunnel wall and one where it protrudes into the tunnel space16. It has been hypothesized that molecules bound in the A site could shift the equilibrium between these two states, impacting nascent chain movement16,17,55. In the presence of IDB-001, the equilibrium of A3908 is shifted towards the conformer that protrudes into the tunnel volume, thus coming closer to the compound and potentially hydrogen bonding to the repositioned side chain of the −1 aspartic acid (Fig. 3i). Together, our comparative analysis shows that interdictors cause distinct changes in the PTC that allow them to bind and specifically engage with the nascent chain. Our results and previous insights from earlier mechanistic studies of ANS2,39 lead us to conclude that interdictor binding is determined by three key elements: the core pyrrolidine affords binding affinity to the PTC of the ribosome, while the peptide-facing distal R substituents confer differential biochemical selectivity to the nascent chain. On the other end of the molecule, the methoxyphenyl group likely impedes accommodation and transpeptidation of incoming A-site tRNAs.

Interdictors reduce cancer cell viability and differentially activate the ribotoxic stress response
We next sought to determine how these designed context-dependent translation inhibitors impact cancer cell fitness. In viability assays using HCC-1143 (TNBC) cells, both IDB-001 and IDB-002 inhibited cell proliferation at nanomolar concentrations (Fig. 4a and Table 2). IDB-002 treatment showed a dose-response similar to that of ANS, while IDB-001 displayed weaker activity (Fig. 4a). Given their role in inhibiting translation elongation, we asked whether these compounds would stimulate the RSR pathway, as has been documented for ANS in eukaryotic cells33,56–58. Intermediate concentrations of ANS, which lead to a high frequency of ribosome collisions, stimulate the RSR and trigger JNK-mediated apoptotic signaling33. To determine whether the differences in potency were associated with distinct effects on the RSR, we monitored JNK phosphorylation following compound treatment. ANS and IDB-002 rapidly induce robust phosphorylation of both p46 and p54 JNK isoforms within 15 min in both HCC-1143 and HEK293T cells, consistent with strong and immediate RSR activation (Fig. 4b and Supplementary Fig. 10a, b). In contrast, IDB-001 and HHT did not lead to any detectable JNK phosphorylation. Extending treatment duration revealed that IDB-001 can lead to modest JNK and p38 phosphorylation after 2 h at a high concentration (10 µM), but the magnitude of phosphorylation is significantly lower than observed for IDB-002 treatment, suggesting that IDB-002 might cause more ribosome collisions than IDB-001 (Fig. 4c). Indeed, when we performed a global metagene analysis of the ribosome footprints centered around identified pause sites, we observe a stronger peak 5´ to the primary pause site, corresponding to trailing or collided ribosomes, for IDB-002 treatment than for IDB-001 treatment (Fig. 4d). While the RSR is differentially activated, both IDB-001 and IDB-002 treatment led to phosphorylation of eIF2α (a marker of the integrated stress response) after 8 h at high (10 µM) concentrations (Fig. 4c). These data confirm that interdictors with unique polypeptide sequence preferences can inhibit cancer cell viability either concomitant with, or independent of the RSR.

IDB-003 inhibit tumor growth of MDA-MB-231 xenografts in vivo and depletes short-lived oncoproteins
To enable in vivo studies to establish proof-of-concept for this therapeutic modality, we developed IDB-003, a second-generation analog of IDB-002 optimized for oral dosing. IDB-003 retains the core ANS scaffold and PTC-nascent chain binding mode of IDB-002 but replaces the metabolically labile methoxy group with an oxazole moiety, improving metabolic stability and bioavailability59 (Fig. 5a). Ribosome profiling confirmed that IDB-003 maintains a similar context-dependent stalling signature, especially in the −1 position, to IDB-002 (Figs. 1g, 5b). IDB-003 more potently inhibited cell proliferation in MYC-dependent cancer cell lines, including prostate (22Rv1), colorectal (LS411N), HR+, HER2- breast (MCF7) and TNBC (HCC-1143) when compared to fibroblasts (MRC5), with EC50 values in the nanomolar range, generally 2-5-fold more potent than its predecessor IDB-002 (Fig. 5c and Table 2).

Given the MYC-dependent nature of these cell lines, and that the MYC protein has a very short half-life in highly proliferative cells, we asked whether treatment with interdictors would lead to the depletion of MYC as well as other rapid turnover oncogenes such as CCND1 whose expression requires consistent translation. Indeed, treatment of MCF7 cells with 1 µM IDB-003 led to rapid depletion of CCND1 evident by 1–2 h and reduction in MYC levels observable after 2 h of treatment (Fig. 5d) while treatment with 10 µM IDB-003 led to rapid depletion of MYC in <4 hours (Supplementary Fig. 10c). In contrast, the abundance of the longer-lived proteins CDK4 and tubulin remained stable over the same time course. These kinetics parallel those observed for saturating cellular amounts of cycloheximide (CHX), a non-selective translation inhibitor that binds the ribosome E site5,60 (Fig. 5d). When comparing the three interdictors side-by-side, the kinetics of MYC and CCND1 depletion generally correlate with cellular EC50: IDB-003 led to fastest depletion, followed by IDB-002, then IDB-001 (Supplementary Fig. 10c).

We next assessed RSR activation and found that IDB-003 rapidly induced JNK phosphorylation in a manner similar to IDB-002, consistent with collision-induced stress (Supplementary Fig. 10d). Ribosome footprinting further demonstrated that IDB-003 stalled ribosomes within the coding sequences of MYC, CCND1 and CDK4, supporting a direct mechanism for their depletion (Supplementary Fig. 11). In addition to stalling in the 5´ end of the MYC CDS, we observed increased ribosome occupancy in the MYC 5´ UTR (Supplementary Fig. 11a). MYC translation is controlled by non-canonical translation initiation mechanisms, such as usage of an upstream CUG start codon and possibly an internal ribosomal entry site (IRES) element61,62. The increased ribosome footprints in the MYC 5´ UTR upon interdictor treatment may be due to occlusion of the canonical (and CUG) start codons by ribosomes stalled early in the CDS diverting scanning complexes to uORFs. To test whether the acute loss of MYC we observed was functionally linked to growth inhibition, we quantified MYC levels by homogeneous time-resolved fluorescence (HTRF) after 2-h IDB-003 treatment in HCC-1143 cells. MYC depletion by IDB-003 closely paralleled concentration-dependent loss of cell viability, linking MYC loss to growth inhibition in this TNBC model (Fig. 5e). However, since both activation of the RSR/ISR pathways as well as depletion of oncogenes like MYC and CCND1 occur on similar time scales (15 min–2 h; Fig. 4c and Supplementary Fig. 10c, d), we cannot precisely identify the pathway responsible for cell viability defects. In an attempt to untangle the precise mechanism by which cells die, we performed cell viability experiments for our interdictors in combination with inhibitors of the RSR and ISR pathways (the ZAK inhibitor Nilotinib63,64 and GCN2 inhibitor GCN2iB65,66, respectively) and observed no meaningful shifts in the resulting dose-response curves (Supplementary Fig. 10e). This suggests that activation of ribosome surveillance pathways is not the sole driver to the observed cell growth inhibition.

We then turned to an in vivo setting to assess whether these cellular effects would translate to a cell-derived xenograft model. To test the efficacy of IDB-003 on solid tumor growth inhibition in vivo, we chose the highly metastatic and difficult to treat TNBC model MDA-MB-23167,68, which has been shown to be less sensitive to CDK4/6 inhibitors because of robust MYC expression69. After 28 days of twice daily oral dosing (PO BID), we observed 80% tumor growth inhibition (TGI) for mice given a 10 mg/kg dose of IDB-003, and 58% TGI for the group given a 3 mg/kg dose compared to vehicle control (Fig. 5f). RNA-seq analysis of endpoint tumor samples revealed broad transcriptional changes consistent with on-target inhibition of translation elongation. Gene set enrichment analysis (GSEA) of hallmark gene sets identified MYC targets v1 as the most significantly downregulated pathway in IDB-treated tumors compared to vehicle70,71 (Fig. 5g). This molecular signature, together with the observed in vivo tumor growth inhibition, supports a model in which suppression of short-lived oncoproteins, including MYC, is a key driver of efficacy. These results provide strong preclinical evidence that pharmacologic interdiction of translation elongation is a viable approach for targeting MYC-driven cancers in vivo.

Methods
Interdictor synthesis
Detailed methods for chemical synthesis of IDB-001, IDB-002, and IDB-003 are included in the Supplementary Methods.

Cell culture, drugging, and harvesting for ribosome profiling
HCC-1143 breast cancer cells (ATCC) were cultured in RPMI 1640 medium with 10% fetal bovine serum (FBS), 100 U/mL penicillin, 100 U/mL streptomycin and 1% GlutaMax (Gibco). For ribosome profiling experiments, media was replenished 24 h prior to harvesting. When cells reached 70-80% confluency, they were treated with anisomycin (ANS) or interdictor for 60 min at 10 µM (unless otherwise noted). Cells were washed with ice-cold phosphate-buffered saline and lysed in lysis buffer (20 mM Tris-HCl pH 7.4, 150 mM NaCl, 5 mM MgCl2, 1 mM DTT, 1% v/v Triton X-100, 25 U/mL Turbo DNase I). Lysates were incubated on ice for 30 min to allow for DNase digestion and clarified by centrifugation at 20,000 × g for 30 min at 4 °C. Lysate RNA content was quantified with Quant-it™ RiboGreen reagent (Thermo Fisher) on an EnVision microplate reader (Revvity), following the manufacturer’s instructions. Cycloheximide was not used in this study.

Ribosome profiling library preparation
Samples were collected in triplicate for DMSO and 10 µM interdictor-treatment, and duplicates at all other concentrations. Lysates were digested with 3.33 U/µg RNase I (Ambion) for 45 min at room temperature with gentle agitation. Monosomes were then isolated by sucrose cushion, using 450 µL 1 M sucrose in polysome buffer (20 mM Tris-HCl pH 7.4, 150 mM NaCl, 5 mM MgCl2, 1 mM DTT) for 400 µL of digested lysate material. Sucrose cushions were performed with a MLA-130 rotor in an Optima Max-XP ultracentrifuge (Beckman Coulter) at 100,000 × g for 90 min at 4 °C. Pellets were resuspended in resuspension buffer (150 mM NaCl, 20 mM EDTA, 1% Triton X-100, 20 mM Tris-HCl pH 7.5) and incubated at room temperature for at least 10 min. RNA was extracted using Direct-zol RNA miniprep kit (Zymo), according to the manufacturer’s instructions. Ribosome footprint RNA size selection followed a standard workflow82 with minor modifications, including the use of 10% TBE-urea gels (Biorad) and custom sizing markers (17–34 nt). Following overnight gel extraction and ethanol precipitation, RNA was dephosphorylated with T4 PNK (NEB) at 37 °C for 1 h. Ribosome footprint cDNA libraries were subsequently constructed using Ordered Two-Template Relay kits (Karnateq) according to the manufacturer’s recommendations41. cDNA libraries were indexed and amplified with NEBNext Indexing Primers (NEB).

Ribosome profiling data processing
Raw ribosome profiling sequencing reads were first trimmed to remove adapter sequences using Cutadapt v3.583, discarding any reads shorter than 16 nucleotides. The trimmed reads were then mapped sequentially to rRNA, cytoplasmic and mitochondrial tRNA references, followed by alignment to mitochondrial mRNA, mitochondrial DNA, and various noncoding RNA references with Bowtie v1.3.1 and Bowtie 2 v2.4.484,85. Next, any remaining reads were aligned to human mRNA (RefSeq MANE v1.3) and processed through RSEM v1.3.386 for transcript quantification. RSEM quantifications of mRNA-aligned RFPs were used for all downstream analyses. Using the length of each ribosome footprint and the reading frame identified at the 5´ end of the ribosome-protected fragment, the A-site codon was inferred and subsequently used to determine the corresponding peptide sequence in the nascent polypeptide chain. Read processing, genomic coordinate handling, and A-site inference were performed using bedtools v2.30.087 and samtools v1.1388, with downstream analyses implemented using custom Python (v3.10.12) scripts. All raw ribosome profiling sequencing data have been deposited in the Gene Expression Omnibus (GEO) under accession number GSE285904.

Pause site identification and sequence analysis
To identify codon positions at which ribosome occupancy increased in response to compound, we first restricted our analysis to genes with an average coverage exceeding 0.5 reads per codon across replicates. We then adapted a previously described strategy45,89, employing two-tailed Fisher’s exact tests to identify codons displaying significant changes in ribosome occupancy between compound and DMSO-treated samples. Briefly, read counts at each codon were averaged across replicates, rounded to the nearest integer, used to generate a 2 × 2 contingency table comparing the ratio of compound- versus control-derived ribosome footprints at a given codon against the ratio of all other codons in the same gene. Multiple-testing correction was performed using the Bonferroni method. A codon was deemed a pause site if it had an odds ratio greater than 1 (and finite) and its adjusted p-value was less than 0.05. Finally, we used ggseqlogo v0.2.246 to create sequence logos of these pause sites (from positions −7 to 0) by scaling the nascent peptide sequences of the pause sites by the corresponding odds ratio.

Metacoverage and polarity scoring analyses
To examine how interdictor treatment influenced the distribution of ribosome footprints along the length of transcripts, we carried out metacoverage and polarity scoring analyses. First, each ribosome footprint was assigned to the 5′ UTR, the coding sequence (CDS), or the 3′ UTR. A normalized meta-position value was calculated by dividing the footprint’s location by the length of its respective region in that transcript, then shifting these values so that the entire transcript could be represented from meta-position −1 to +2 with: −1 to 0 corresponding to 5′ UTR, 0 to +1 representing CDS, and +1 to +2 representing 3′ UTR. Only footprints from genes with adequate coverage (>0.1 reads per codon) were retained. At each meta-position (rounded to two decimal places), counts were normalized to library size and averaged across replicates.

We next calculated a polarity score for each transcript (adapted from ref. 43), which captures the distribution of ribosome coverage from the start to the stop codon. Specifically, for a CDS of length L codons, the polarity score P is given by: P = (sum(w_i * c_i)) / (sum(c_i)), where w_i = 2 * (i / L) - 1. Here, c_i is the ribosome footprint coverage (read count) at codon i, and w_i is a position-specific weight ranging from −1 at the start codon (i=0) to +1 at the stop codon (i=L). Thus, P varies between −1 (indicating that all ribosomes were positioned at the start) to +1 (indicating that they were entirely clustered at the stop codon).

Differential ribosome occupancy analysis
Ribosome footprints and corresponding nascent peptide sequences spanning four codons (positions −3 to 0) were used to generate count tables corresponding to the number of reads mapping to each unique 4-mer across samples. To identify 4-mers with changing ribosome occupancy in compound-treated versus DMSO-treated samples, differential ribosome occupancy analysis across 4-mers was performed with DESeq2 v1.46.047. 4-mers showing a significant increase in ribosome occupancy (log2 fold-change > 0.5) were scaled according to their fold-change and input into ggseqlogo v0.2.246 to generate a peptide motif logo.

Similarly, the position-weighted matrix analysis was performed by extracting amino acid identities from ribosome footprints and corresponding nascent peptide sequences from nascent chain position (−7 to 0). After filtering for coverage threshold (genes with >0.1 read/codon) and normalizing to library size, log2 fold-change was calculated by comparing each treatment condition to DMSO for every residue at each position.

Selection of 4-mer sequences for the in vitro luminescence assay
To ensure that the majority of the signal from interdiction of the 4-mer containing reporters was derived from interdiction of the 4-mer sequence rather than the HiBit tag we tiled six repeats of each 4-mer before the 11 AA HiBit tag. Due to tiling of the 4-mer sequence in this way, the ribosome will encounter, and present for interdiction, not just the 4-mer of interest but also all four rotations of that 4-mer. Therefore, we created a rotation score metric that summed the log2-fold change for all four rotations of the 4-mer, and chose 4-mers for inclusion in the luminescence assay based on this score. As such the expected level of interdiction, estimated from the ribosome profiling experiments, is based on the entire 24 AA reporter sequence rather than the single 4-mer hit.

Creation of reporter plasmids for the in vitro transcription-translation luminescence assay
The plasmid pT7CFE1 (Thermo Scientific) was digested in rCutsmart buffer with the restriction enzymes XhoI and MscI (New England Biolabs) for 1 h at 37 °C. The linearized plasmid was used as a template for Gibson Assembly together with a gBlock (Integrated DNA Technologies) containing the coding sequence of interest and the HiBit tag, followed by a stop codon. Gibson assembly was carried out using a Gibson master mix (New England Biolabs) at 50 °C for 1 h. 2 µL of the Gibson assembly reaction was used to transform 20 µL of Mach 1 competent E. coli (Invitrogen). The correct plasmid sequence was verified by whole plasmid sequencing (Genewiz).

In vitro transcription-translation luminescence reporter assay
An in vitro translation transcription system was created by combining on ice, for each sample to be measured, 5 µL of HeLa cell lysate (Ipracell), 1 µL of Accessory protein mix (Thermo Fisher), 2 µL of Reaction mix (Thermo Fisher), and 1 µL of HiBit substrate mix, consisting of 1:10 Nanoluc substrate (Promega) and 1:10 LgBit protein (Promega) in Nanoluc sample buffer (Promega). To this mixture was added 2 µL of interdictor dissolved in water at the required concentration. The reaction was started by addition of 2 µL of the relevant reporter plasmid at 110 ng/µL and transfer of the assay mixture to 30 °C within a luminescence-capable plate reader (BMG Labtech, CLARIOstar Plus). The ensuing in vitro transcription-translation reaction was then followed in real time by recording the luminescence intensity of each sample every 108 s. The resulting luminescence time traces were then analyzed in Prism 10 (GraphPad Software) by identifying the linear portion of each trace, corresponding to steady-state protein synthesis, and determining its slope through linear fitting. The slopes of each reaction where then plotted against the interdictor concentration and IC50 values determined by non-linear fitting of the equation “Inhibitor vs. Response—three parameters” within Prism 10.

Generation of stalled RNC complexes for cryo-EM
Stalled RNC complexes for cryo-EM were generated by in vitro translation of non-stop mRNAs similarly as described in (ref. 50): Linear DNA template encoding an internal ribosomal entry site (IRES), followed by a 3xFLAG tag, the Villin head domain90 and the sequence of interest was amplified by PCR using a reverse primer that contained two extra nucleotides carrying a C2´-methoxy modification proximal to the 5´ end to reduce non-templated additions in the subsequent T7 transcription step91.

Linear DNA was added to IVTT reactions (Thermo Scientific 1-Step Human Coupled IVT Kit, 88881) according to manufacturer’s instructions and incubated with HeLa cell lysate for 20 min at 30 °C. HeLa cell lysate was either produced in house using standard protocols (QEDE RNC and QEDE RNC+IDB-001 samples) or purchased from Ipracell (FPAK RNC+IDB-002 sample). Reactions were quenched with 1 mM buffered cycloheximide and clarified by centrifugation for 20 min at 4 °C and 20,000 × g. Reactions were pelleted through a 1 M sucrose cushion containing 750 mM KOAc, 5 mM MgOAc and 20 mM Hepes pH 7.4 at 541,000 × g for 2 h at 4 °C in a TLA100.3 rotor (Beckman Coulter). Reactions were resuspended in 20 mM Tris pH 7.5, 100 mM KOAc, 7.5 mM MgOAc, 0.25 mM spermidine, and 0.01 % NP-40 and incubated with pre-equilibrated M2 FLAG bead slurry (Pierce) at 4 °C for 1 h. Beads were washed with resuspension buffer, including a high-salt wash step with KOAc adjusted to 750 mM before elution with 1 mg/mL 3X FLAG peptide (Sigma). Beads were regenerated with 0.1 M glycine and the re-incubated with the flow-through from the previous step. The eluates were combined and concentrated in a 100 kDa cutoff centrifugal spin filter (Amicon) to remove FLAG peptide, smaller contaminants and to exchange the buffer to cryo-buffer (20 mM Tris pH 7.5, 100 mM KOAc, 7.5 mM MgOAc, 0.25 mM spermidine, 0.05% Octyl-β-D-glucopyranoside (Thermo Scientific)).

Cryo-EM grid preparation, data collection, and processing
Between 150 and 300 nM of purified RNC complexes were incubated on ice with 50 µM of compound that has been pre-diluted in cryo buffer for 30 min. 4 µL of sample was applied on glow-discharged Cu 2/1 300 mesh + 2 nm carbon grids (Quantifoil) and plunge frozen in liquid ethane using a Vitrobot (Thermo Scientific), using a blot force of 0 and a blot time of 1 s. Grids were imaged at the LSI Cryo-Electron Microscopy Lab at the University of Michigan. Data were collected on a Titan Krios microscope (Thermo Scientific) operating at 300 kV and equipped with a Gatan K3 direct electron detector and a Bioquantum imaging filter using a customized version of SerialEM v4.1.2.1 data collection software. Movies were acquired using a pixel size of 0.834 Å/px, a total dose of 50 e−/Å2 and using a nominal defocus range between -0.8 µm to −1.5 µm (Table 1). All data processing was carried out in Cryosparc v4.592 and is schematically outlined in Supplementary Fig. 6. After motion correction and CTF estimation, particles were picked using the blob picker with a particle size of 250–300 Å. After particle extraction and 2D classification, ribosome classes were refined to a consensus structure that was used as a basis for 3D classification without alignment using a filter of 12 Å to identify conformationally and compositionally distinct ribosome classes. Repeated rounds of 3D refinement and 3D classification without alignment with focus on each tRNA yielded the final classes that are shown in Supplementary Figs. 7, 9. Classes of interest were refined to high resolution by performing per-particle CTF correction and reference-based motion correction, followed by non-uniform refinement. To resolve additional detail and guide model building, local refinement was carried out for the PTC and the anticodon region using a 50 Å diameter mask around each region of interest. Resolution of each reconstruction was assessed using the FSC=0.143 criterion93.

Final, unsharpened maps of classes representing the POST state were used for atomic modeling in Isolde v1.894 and Coot v1.1.195, using PDB 8GLP as a starting model39. For the IDB-001 QEDE RNC, all residues of each chain were manually checked, keeping residues in peripheral regions with low density to allow for a somewhat complete consensus model. Newly built residues include an ARG-containing loop in the 60S ribosomal protein L10 that contacts the CCA of the tRNA. The obtained model was placed into the other three maps and locally adjusted in the regions of interest before minimizing the entire model in Isolde v1.8. Individually built regions include the tRNA itself, the nascent chain and the mRNA for each complex. The mRNA and nascent chain sequences were inferred from the no-go construct used to generate the sample and checked against the tRNA and mRNA densities. B-factor sharpened maps were used for placing water molecules, ions and ligands for each complex individually. Final macromolecular refinement was carried out in Phenix v1.21.296, using the sharpened maps and restraints generated in eLBOW for modified nucleotides and compounds in addition to reference restraints generated from the Isolde-minimized model. Maps and models were visualized and analyzed and structure figures created with ChimeraX v. 1.897.

Cell culture and western blot analysis
All cell lines used in this study were purchased from ATCC and cultured using recommended protocols: 22Rv1 (ATCC, CRL-2505), MCF-7 (ATCC, HTB-22), HCC-1143 (ATCC, CRL-2321), LS411N (ATCC, CRL-2159), and MRC5 (ATCC, CCL-171).

Western blot analyses were performed by plating 5 million cells in 15 cm dishes with the appropriate media and leaving the cells to adhere overnight. The next day, compounds were diluted in 100% DMSO and directly added to each dish, with a final concentration of 0.5% DMSO or less. Sample time points were rinsed with 1 mL of cold PBS at time of collection, scraped and pelleted (5 min at 500 × g). The PBS was then aspirated off and cell pellets frozen in LN2. Frozen cell pellets were lysed on ice for 20 min in 50 µL of RIPA buffer (Thermo Scientific, 89901) supplemented with HALT Protease Inhibitor with EDTA (Thermo Scientific, 78429), HALT Phosphatase Inhibitor (Thermo Scientific, 78420), and benzonase (Sigma-Aldrich, E1014-25KU). Lysates were clarified by centrifugation at 17,949 x g for 10 min. After clarification, supernatants were quantified by BCA analysis (Thermo Scientific, 23225) or equivalent loading and denatured in SDS-PAGE dye. Proteins were resolved by 4–15% Criterion TGX midi protein gels (Bio-Rad, 5671084) and transferred to PVDF membranes using a Trans-Blot Turbo transfer system (Bio-Rad). Non-phosphorylated (MYC, Tubulin, CDK4, CCND1, eIF2α, FLAG) membranes were blocked with 5% nonfat dry milk (Cell Signaling, 9999S) in TBST with primary antibody overnight with gentle rocking at 4 °C, while phosphorylated (P-JNK, P-P38, P-eIF2α) membranes were treated similarly except for using 5% BSA (Cell Signaling, 9998S) in TBST. After overnight incubations, blots were washed three times for 5 min in TBST and then incubated with secondary antibodies at RT with gentle rocking for 2 h. Membranes were washed again with TBST before being developed using SuperSignal West Femto Maximum Sensitivity Substrate (Thermo Scientific, 34096) and imaged on an iBright system (Invitrogen). Primary antibodies used in this study: MYC (Cell Signaling Technology, 13987S), P-JNK (Cell Signaling Technology, 4668S), α-Tubulin (Abcam, AB7291-1001), FLAG M2-HRP (1:5000; Millipore Sigma, A8592), CDK4 (Cell Signaling Technology, D9G3E), CCND1 (Cell Signaling Technology, E3P5S), eIF2α total (Cell Signaling Technology, 9722S), P-eIF2α (Abcam, ab32157) and P-P38 (Cell Signaling Technology, 28B10). Secondary antibodies: anti-rabbit-HRP (Cell Signaling Technology, 7074) and anti-mouse-HRP (Cell Signaling Technology, 7076). All antibodies were used at 1:5000 dilution in 5% milk or BSA as indicated above.

Homogeneous time-resolved fluorescence assay
HCC-1143 breast cancer cells were plated in black Bio-One CELLSTAR 96-well, cell culture-treated, flat-bottom microplates (Greiner) at concentrations between 2000 and 10,000 cells/well in tissue culture media and incubated overnight in standard tissue culture incubator (37 °C, 5% CO2). Once cells adhered, compounds resuspended in 10% DMSO were added to each well containing 100 µL of media for a final concentration of 0.5% DMSO. After 2 h of incubation the assay was run using the Revvity HTRF Human c-Myc Detection Kit (Part # 63ADK053PEH) following manufacturer’s procedure. Data were read out on an Envision fluorescent plate reader (Revvity). To calculate IC50 values, each plate is background-subtracted and normalized to DMSO only control wells for a % signal compared to control. Non-linear regressions for each compound and cell line were performed to obtain the IC50 value.

Cell viability assay
Indicated cell lines were plated in black Bio-One CELLSTAR 96-well, cell culture-treated, flat-bottom microplates (Greiner) at concentrations between 2000 and 10,000 cells/well in tissue culture media and incubated overnight in standard tissue culture incubator (37 °C, 5% CO2). Once cells adhered, compounds resuspended in 10% DMSO were added to each well containing 100 µL of media for a final concentration of 0.5% DMSO. Co-treatments with RSR/ISR inhibitors were performed with 1 µM ZAKi Nilotinib63,64 (MedChemExpress HY-10159) and 2 µM GCN2i GCN2IB65,66 (MedChemExpress HY-112654) added concurrently with interdictor. After 72 h of incubation, viability was assessed using established protocols for Cell Titer-Fluor assay (Promega). Briefly, the media was removed from the plates, cells gently rinsed with PBS, and a 1:1 mix of PBS and fluorescent substrate was added to the plates before incubating for 60 min at room temperature with orbital shaking. Finally, viability was quantified per kit instructions using an Envision fluorescent plate reader (Revvity). To calculate EC50 values, each plate was background subtracted and normalized to DMSO only control wells for a % viability compared to control. Non-linear regressions for each compound and cell line were performed to obtain the EC50 value.

MDA-MB-231 xenograft study in mice
Efficacy study for IDB-003 in human TNBC MDA-MB-231 tumor-bearing, 6–8-week-old female BALB/c nude mice (GemPharmatech., Ltd) received ethical approval and was performed at Pharmaron (Beijing, China). All procedures related to animal handling, care, and treatment in this study were performed according to guidelines approved by the Institutional Animal Care and Use Committee (IACUC) of Pharmaron and in compliance with the guidance of the Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC). In addition, all portions of this study were performed at Pharmaron and adhered to the study protocol provided or approved by the sponsor and applicable standard operating procedures (SOPs). Animals were quarantined for 7 days before the start of any experimental procedure. The general health of the animals was evaluated by a veterinarian, and complete health checks were performed. Animals with abnormalities were excluded prior to the study start. General procedures for animal care and housing were in accordance with the Commission on Life Sciences, National Research Council, and standard operating procedures (SOPs) of Pharmaron, Inc. The mice were kept in laminar flow rooms at constant temperature and humidity with 4–5 animals in each cage. Animals were housed in polycarbonate cages which were the size of 300 × 180 × 150 mm3 and in an environmentally monitored, well-ventilated room maintained at a temperature of 23±3 °C and a relative humidity of 40–70%. Fluorescent lighting provided illumination approximately 12 h per day, lights on 8 A.M. and off at 8 P.M. Animals had free access to irradiated, sterilized dry granule food during the entire study period. Hydrogel supplementation was offered to animals if significant body weight loss was observed. Sterile drinking water in a bottle was available to all animal ad libitum during the quarantine and study periods.

The MDA-MB231 tumor cell lines were maintained in vitro as monolayer in L-15 medium supplemented with 10% heat-inactivated fetal bovine serum at 37 °C in an atmosphere of 100% air. The tumor cells were routinely sub-cultured before confluence by trypsin-EDTA treatment, not to exceed 4–5 passages. The cells growing in an exponential growth phase were harvested and counted for tumor inoculation. Each female BALB/c nude mouse was inoculated subcutaneously on the right flank with MDA-MB-231 tumor cells (1×107) in 0.1 mL medium and matrigel mixture (1:1 ratio) for tumor development. All animals were monitored for tumor growth conducted with a caliper and recorded twice a week for the 28-day period, or until the maximal tumor size was reached (tumor volume > 10% animal body weight). In addition, all animals were monitored for irregular behavior such as changes in mobility, food and water consumption (by cage side checking only), body weight (BW), eye/hair matting or any other abnormal condition. Any mortality and/or abnormal clinical signs were recorded. Groups and treatments were started when the mean tumor volume reached 150–200 mm3. Based on the tumor volume and body weight, mice were randomly assigned to respective groups such that the average starting tumor size and body weight was the same for each treatment group. Mice were provided with vehicle (5% DMSO/95% (20% HP-β-CD in water); n=6 animals) or IDB-003 dissolved in vehicle by oral gavage. For the group dosed with 3 mg/kg IDB-003 (n=8 animals), the mice received treatments twice daily for 28 days. The group dosed at 10 mg/kg (n=8 animals) were given a 2-day dosing holiday after 11 days of treatment (11 days on, 2 days off) for the 28-day period. No clinical observations were noted, no mortalities occurred, and no mice reached the maximal tumor burden allowed over the 28-day study. To analyze TGI, the following formula was used: TGI = 100 * (1 − ((TV treated final - TV treated initial) / (TV Vehicle final - TV Vehicle initial))).

Tumor RNA-sequencing library preparation
Tumor samples were first flash frozen with liquid nitrogen and pulverized to ensure thorough disruption. Total RNA and protein were extracted using the AllPrep RNA/Protein kit (Qiagen), following the manufacturer’s protocol. RNA fractions were subsequently subjected to additional purification and DNase treatment with the RNA Clean and Concentrator kit (Zymo Research) to remove residual genomic DNA and improve RNA integrity. Strand-specific cDNA libraries were generated using the NEBNext Ultra II Directional RNA Library Prep Kit (New England Biolabs) according to the manufacturer’s instructions. Total RNA was depleted of rRNA with the NEBNext rRNA Depletion Kit v2 (New England Biolabs). Libraries were PCR-amplified with NEBNext Multiplex Oligos for Illumina and size-selected with AMPure XP beads (Beckman Coulter).

Tumor RNA-sequencing data processing
Paired-end sequencing reads were aligned to the human RefSeq MANE v1.3 transcriptome using HISAT298 with default parameters. Transcript-level read counts were generated across RefSeq MANE annotations using featureCounts99. Differential expression analysis was performed between treatment and control groups with DESeq247. To assess pathway-level changes, significantly regulated genes (adjusted p-value < 0.05) were subjected to GSEA using the MSigDB Hallmark gene sets70,71. All raw RNA-sequencing data have been deposited in the GEO under accession number GSE309226.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript „Context-dependent translation inhibition as novel cancer therapeutic modality” describes the design, development and functions of small molecules that can inhibit protein synthesis in a peptide sequence-dependent manner, by binding to the PTC of the large ribosomal subunit. The authors tested two novel molecules based on anisomycin and identified stalling motifs within nascent peptides. CryoEM was used to identify the binding site and potential decisive structural changes. Finally, they also tested their novel components in different cancer cell lines and in xenografts in mouse models, and observed a potential therapeutic strategy to inhibit cancer growth. The submitted work presents a fairly complete description of the design, the in vivo and vitro biochemical characterization, structural studies and experiments regarding the potential of cancer therapy by these novel interdictors. In my opinion, this is a really interesting manuscript that is significant for the scientific community. It is well written, the methods are described in detail and the figures are nicely prepared. However, there is one aspect that I am confused about concerning the Myc inhibition.\nThe authors identified motifs that are associated with the inhibition by IDB-001 and performed the cryoEM studies with these potential stall sites. According to the story line of the manuscript, IDB-001 preferentially inhibits FTED motifs with acidic amino acids. Consequently, DSEEEEQEDE was identified as a potential stall site for 001 and this motif was then also used for the cryoEM structures. However, in Figure 5B, the Western blots indicate that 002 is more potent than 001, which is also confirmed by Figure S9. The concentration of 001 used for the Western Blots (5B) was 30 µM and for 002 only 10 µM. Figure S9 shows the 10 µM experiments for 001, where the inhibition is less efficient. This may be somewhat misleading as it is also not addressed in the manuscript. This also raises questions about the potential stalling motif (at least within Myc), which does not seem to be that good. Alternatively, there may be a peptide sequence within Myc that enables a stronger inhibition by IDB-002. Did you find Myc in the ribosome profiling data (analogous to H2BC17 or ANLN) for 001 or 002? I think this aspect needs some clarification!\nAlong these lines: how well did Anisomycin inhibit Myc expression?\nAt the beginning of the results, the authors describe the design of the novel compounds very superficially. Was it a purely rational design based on the structure of the ribosome? No molecular dynamic simulations or similar approaches to assist the design? No failed attempts? I have always had the impression that it is really difficult to tailor known molecules to improve/customize their function.\nThe in vitro experiments are based on reporter sequences carrying 6 repeats of the stalling sequences. Why 6? Is one or two not sufficient? Maybe it would also be interesting to include the potential stalling sequence of Myc and compare it with the identified motifs. How does in vitro compare to in vivo. It should be possible to create a reporter mRNA with the respective motifs and express them in cells (either directly by RNA transfection or expressed from a plasmid). This would also provide an idea of how strong the inhibition is at certain sites. Perhaps this could also provide an idea about the stalling elements of Myc (the point I raised earlier).\nMaybe I missed it: do the compounds bind the PTC in the absence of stalling motifs or are they required for binding? This might allow us to speculate about the mode of action.\nDo the cell lines tested (22RV1, HCC1143,…) express different levels of Myc, since 22RV1 or LS411 require higher levels of the compound 001?\nVery minor:\nPage 1: I don´t know if this intentional but did you mean “selected protein targets” instead of “select protein targets”.", "reviewer_2": "The manuscript “Context-dependent translation inhibition as a novel cancer therapeutic modality” by Paige D. Diamond et al. presents a study aiming at development of so-called interdictor molecules, context-specific inhibitors of protein synthesis as potential cancer drugs. Specifically, interdictors are small-molecule inhibitors of the human ribosome that target the beginning of the polypeptide exit tunnel at the peptidyl transferase center, with sequence specificity to the last few amino acids added to the nascent polypeptide chain. The authors use a combination of ribosome profiling, biochemistry and cryo-EM of the human ribosome to demonstrate the context specific inhibition with anisomycin (existing antibiotic) and three designed variants (IDB-001, IDB-002 and IDB-003). In addition, they test the potential of using IDB-003 for the treatment of MYC-related cancer in a mouse model.\nGeneral comments\nThe manuscript is based on a very interesting concept of using context-specific inhibition of the human ribosome to target “un-druggable” protein targets (e.g. intrinsically disordered proteins or protein regions) in their making on the ribosome. The bacterial ribosome is a main target for antibiotics, but there are currently only few approved drugs that target the human ribosome.\nThe manuscript is in general well written and the illustrations are clear. The authors make use of an impressive array of methods to characterize the effect of interdictor molecules in vitro and in vivo.\nMajor concerns\nThe four presented cryo-EM structures of nascent-chain complexes of human ribosomes with or without interdictors are all at high resolution. However, there are a number of severe issues with the deposited maps and models. The models need to be revised and the appropriate maps provided.\n• There are multiple maps for each model and it is unclear which one is what. The unsharpened map that according to the manuscript text was used for modelling is lacking for three of the structures.\n• The provided sharpened maps are over-sharpened in some important regions (lower resolution regions such as the nascent chain and the mRNA), making the interpretation challenging. According to the manuscript, these maps were used for automated placement of waters. As a result, over-sharpened regions have many unconvincing and unlikely waters, and many of them are clashing with the structure. In particular there are many waters way too close to IDB-001 or the nascent chain in 9O3X, which may explain the much higher clash score in this structure. This may also be the case in the other structures and in other regions. Other waters are placed in density that resembles a base (see next to A3908 and U4399). The waters need to be revised e.g. using the coot validate waters tool to remove waters with clashes or low signal.\n• Details are lacking for the local refinement around “regions of interest”. Please specify which are these regions and how the corresponding masks were generated. Inspection of the locally refined maps does not show any clear improvement. For the nascent chain, this map looks worse. It is also not clear from the text to what extent these maps were used for interpretation.\n• The mean B-factors are very high in all the structures. From looking at the maps provided the reason might be over-sharpening and/or including chains that have barely any density. Many regions do not have supporting density (look at the very low atom inclusion values of many chains in the model validation report), thus the high B-factor and low atom inclusion values.\n• Some of the conformational changes described in Figure 4 are not correctly modeled, partly linked to misplacing of waters (detailed below).\n• Please clarify the model building procedure. The inclusion of chains that lack density suggests that the model was only manually inspected in the regions of main interest, this has to be clarified.\nThe parts of the manuscript that is based on interpretation of the cryo-EM structure over-states what can be seen in the maps. The authors need to revise the text to clarify that the structures according to the attached maps do not show clear evidence of sequence-specific inhibition. They also need to provide clear evidence as figures with un-trimmed maps that in an un-biased way show what can be seen and not.\n• In the results referring to Figure 3, the authors state that “side chain positions of the four residues in contact with the compound (in the 0, -1, -2, and -3 positions) could be assigned.”. Inspection of the provided maps does not support this, only the backbone is clearly assignable.\n• Similarly, referring to Figure 4, the authors state that the identity of the nascent chain positions 0 to -3 could be well modeled. However, the density is very poor and only D-1 is clearly visible in the map.\n• It is unclear if the conclusion of sequence specific stalling was drawn from the peptide sequence in the PTC or from the mRNA sequence. Please clarify how the authors decided what to model.\nThe cryo-EM processing workflow and cryo-EM map validation is presented for one of the structures in Supplementary Figures 7 and 8, but the corresponding figures for the other three structures are missing and need to be added. Also, the cryo-EM methods need to be clearly specified for each of the complexes. The ribosome concentration, number of frames, dose rate and total exposure time need to be specified for each imaged complex.\nMinor general concerns\n• The error bars in graphs are not explained in the legends. Please add an explanation and provide information about the number of replicates.\n• Several figures contain tables. Please make separate tables unless clearly motivated.\nSpecific comments to the text:\nPage 2:\n• Paragraph 2: Please re-write to be clear about what relates to bacterial versus human ribosomes. The sentence starting ”There is only one documented drug-like molecule binding to the NPET…” is too long and difficult to follow.\n• Reference 18: This is about the exit tunnel of bacterial ribosomes, please add some reference that clarifies if the same is true for human ribosome.\n• Paragraph 3: You state that “An alternate mechanism by which translation inhibition has been shown to impact cancer cell viability is mediated through stress response pathways that lead to apoptosis, as has been documented for anisomycin, further confirming translation inhibition as a therapeutic strategy even in the absence of biochemical selectivity.” It is not clear why it confirms it as a therapeutic strategy. Please clarify why this would not also affect “normal” cells.\nPage 3: The final sentence is un-clear. Please clarify what “historically undruggable targets with high validation” means.\nPage 4-5 and Figure 1:\n• When comparing IDB-001 and ANS, IDB-001 shows enrichment of acidic residues but also positively charged residues. The latter one is suggested to be due to its weaker overall inhibition. If that is the case, the acidic residue enrichment is then less persuasive. This is particularly the case since the authors state that ANS strongly disfavors positively charged residues (when compared to DMSO), but IDB-001 also disfavors them. Further down the authors state “Notably, this enrichment disappears when IDB-001 is compared to DMSO” probably referring to positively charged residues, but it is unclear. Please improve the clarity of this paragraph.\n• Figure 1B: it is difficult to differentiate the curves, in particular the blue one. Also, unclear if the shade indicates error bars.\n• Figure 1H: Indication of codon positions under the figure would improve clarity.\nPage 5-6 and Figure 2:\n• Figure 2D shows an example of luminescence time traces. The rest of the traces for the other reporters should be added as a supplementary figure.\n• The legends of Figure 2E-F legends should present how errors are calculated and how many data replicates were used.\nPage 6-7 and Figure 3:\n• Please clarify that “Similar to ANS30, the core binds in a pocket…” refers to both compounds.\n• The statement that ”the methoxyphenyl forms p-stacking interactions with C4398 as it extends towards the tRNA (Figure 3B), all consistent with previous reports …” should preferably be supported with a supplementary figure showing a comparison with anisomycin.\n• At the end of this section (page 7, middle of the page) the two last sentences are repetitive and should be revised.\n• The inset in Figure 3A does not really add much. Possibly using the same style as Figures 3D-E but with the same camera view as the current inset could be more helpful.\n• Please clarify what maps are shown in Figures 3D-E. Comparison with the provided maps suggests that these are trimmed around the model, which in such case is misleading.\n• As commented above, there is no density for F-3. Figure 3F does not add any additional information to Figure 3E, and the surface display may confuse readers to believe that this is a map. Please remove. This side chain lacking density also seems to be the basis for the statement about the “hook-like conformation”. What is the evidence for this?\n• Several statements are not supported by the maps, e.g. “Despite the inherently dynamic nature of the nascent chain in the exit tunnel, backbone and side chain positions of the four residues in contactwith the compound (in the 0, -1, -2, and -3 positions) could be assigned.” and the final sentence “These structures show small molecule interdictors can engage in sequence-selective interactions…”. These statements must be supported with clear evidence in maps from which the sequence is clear, or removed.\nPage 7-8 and Figure 4:\n• The authors suggest that the complementarity of the drug molecule rearranges the peptide chain to form new high-affinity interactions. This is a bit overstated considering that only D-1 has good density.\n• The authors indicate that IDB-001 causes C4398 and C4399 to move by “several angstrom”. This should be specified more clearly. “angstrom” should be changed to “Å” or “Ångström”. Position 4399 is U, not C (typo). In addition, U4399 seems to have both conformations (the new described and the same as in the absence of the drug). Instead, the authors have modeled two waters in that density. This should be revised and shown in the figure.\n• The authors discuss how A3908 is shifted towards the “bottom” conformer, closer to the compound. While this is supported by the map, there is actually density for both conformations in both of the structures (with and without the compound) but the authors have modeled waters in the alternative conformation. Please correct the model in agreement with the density for an alternative conformation of the base, not waters.\n• The authors also discuss that U4452 alternates between two conformations in the absence of the compound. The map shows no density for this base, so the base must be dynamic rather than showing only two conformations. This does not affect the conclusion that the compound stabilizes one single conformation of this base.\n• Figure 4A-B: Many waters do not have supporting density here, see comments above.\n• Figure 4C-F: Please indicate in the legend how the structures were aligned.\n• Figure 4D-F: Supplementary figures showing the density for these regions should be provided and fixed according to previous comments.\nPage 9-10 and Figure 6:\n• The authors do not specify where they think IDB-002 would stall ribosomes translating MYC, which then does not really relate with the claimed specificity. Please clarify. Can the defined logo be found in the MYC gene?\n• The authors indicate that IDB-003 shows a similar pattern of context-dependent inhibition as IDB-002 (Figure 1G and Supplementary Figure 10B). This is not supported by the data, as only the -1 position has a similar pattern, there is no clear specificity in the other positions.\n• IDB-003 seems less specific than IDB-001 and -002, and in general, only showing specificity for small amino acids in position -1. This suggests that IDB-003 may affect most genes. Please clarify if and why you think that this inhibition relates to MYC.\n• Figure 6: Please spell out SEM in the legend.\nPage 11-13:\n• There are many buzz-words in the discussion. Please reduce these vague statements, e.g. “a more advanced tool molecule”.\n• The authors indicate that IDB-003 is highly effective at “well-tolerated oral doses”. Where is this shown? In the methods section it is indicated that all animals were monitored for changes in several parameters. Is there such data to support this claim?\n• The authors indicate that “these data validate our approach of sequence-selective interdiction of protein synthesis as a powerful therapeutic strategy for MYC-driven cancers”. As mentioned above, this needs to be better supported.\n• The authors mention again that the approach is sequence-selective to MYC, but this would need to be supported by data.\n• The statement ”Similar considerations also explain the observed deenrichment of certain sequences that contain bulky aromatic residues, as they are likely to clash sterically with the molecule in the PTC (Figure 1I-J).” would need to be supported by a supplementary figure visualizing how such bulky residues would make clashes.\n• The authors make a statement eluding to similarities between interdictors and PROTACS in ”substoichiometric or catalytic mode of action.” Please clarify this sentence; it is unclear which stoichiometry the authors refer to. Here it would actually be interesting to discuss the stoichiometry of inhibited and trailing ribosomes, interdictors and different nascent chains.\nMethods:\n• Page 16: The authors indicate the luminescence assay was performed in a luminescence-capable plate reader from BMG Labtech. Please specify the specific instrument used.\n• Page 17: Please spell out IRES.\n• Page 17: Why is the cryo-buffer in square brackets when the authors used parenthesis before?\n• Page 19: The authors indicate two numbers for relative humidity, likely a typo.\n• Page 19: A “2-day holiday” does not seem like a correct term to use here.\n• Chemical synthesis section: The authors use calc’d to specify the m/z. Is this a typo?\nOther comments:\n• In the abstract the authors use “~” next to the reported resolution. This could be removed.\n• Supplementary Figures are not mentioned in order in the text. There is a jump from Supplementary Figure 6 to 9 and 7 and 8 are mentioned much later only in the methods.\n• Supplementary Figure 2 is very low resolution and difficult to judge.\n• Supplementary Figure 8: The local resolution should be provided for the main map, not only the locally refined. The inset is misleading, as the resolution for the nascent chain is clearly not 1.9 when looking at this region of the map (looks more like 3.5 Å).", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "In this study, P.D. Diamond and colleagues used structure-based drug design to propose small molecules called interdictors, that selectively slow translation elongation of specific sequences in human ribosomes. They used ribosome profiling, cryo-EM analyses and in vitro translation assays to characterize and cross-validate the stalling sequences that are specific to their designed pharmacophores. They also show that translation of the pro-proliferation MYC gene can be specifically impeded by these interdictors in vitro (on purified ribosomes), in cellulo within Myc-dependent cancer cell line and finally in vivo, using human triple-negative breast cancer xenografted mice.\nOverall, the study appears well designed, with many complementary techniques that convincibly validate the authors’ findings, both in vitro and in animal models. Their work represents yet another solid proof that ribosomes and translation are worth investigating as therapeutic targets, and the molecules they designed might prove extremely promising to fight against the vast panel of MYC-related cancers. Since I am not an expert in chemistry, I can not evaluate the drug design process herein presented. However I believe that this manuscript is worth publishing in Nature Communications, provided that the following comments are addressed:\n- The first part of the manuscript is about the extensive in vitro/in cellulo characterization of the two compounds IDB-001 and IDB-002, which seem to be efficient to stop the translation of specific sequences, including MYC’s acidic stretch DSEEEQEDE. However, the in vivo validation on the xenografted mouse was performed using a third interdictor, IDB-003, which only appears late in the results section and has not undergone the same exhaustive validation as the other two compounds. This is confusing, and readers may wonder if IDB-001 and IDB-002 were tested on mouse models and found to be ineffective. If this is the case, I believe the authors should clearly justify their choice of the third compound IDB-003, and re-shuffle the corresponding results section so that the ribosome profiling and MYC expression assays (shown in figure S10) are presented earlier in the text. Otherwise, the current elliptical style slightly undermines the strength of the reported study.\n- A CryoEM analysis of the third compound represents a significant amount of additional work and is probably out of the scope of this manuscript, thus, to reinforce their findings, could the authors also test the effect of IDB-003 on RSR, by WB experiments?\nMinor comment:\nThe composition of the tetrapeptide/4-mers sequences should be described earlier (p.5) to improve clarity.", "reviewer_5": "Diamond, Sauer, et al. report the exciting discovery of first in class molecules that can inhibit protein synthesis in a specific manner dependent upon the polypeptide sequence in the peptidyl-transferase center (PTC). The findings presented in this manuscript are an important step toward selectively targeting the translational machinery with the potential to specifically inhibit the growth of tumors, which could be programmed to combat other diseases. The authors conduct transcriptome-wide ribosome profiling to demonstrate the selective stalling of the ribosome, which, coupled with structural studies, illuminates the potential selective mechanism of action at the molecular level. They show that the compounds can inhibit cancer viability potentially through repressing of MYC translation and/or ribosomal stress response. Finally, they demonstrate in vivo efficacy of tumor growth inhibition with a third orally available compound. This study is of interest to the broad readership of Nature Communications. However, while this work is a valuable step towards harnessing the power of targeting selective translation, it requires additional experimentation to solidify the proposed claims mechanism of action and target specificity.\nMajor Points:\n1. While the authors provide insight into the specificity of the stall sequences with interdictor treatment, there is a lack of validation at the proteome level. This is key to demonstrating that their compounds result in selective and specific changes at the protein level, which may mechanistically underpin the phenotype on cancer cell line viability. The authors should show global proteomic changes in their cell line models and analyze how those changes overlap with the observed stall sites transcriptome-wide.\n2. The authors fail to show the kinetics and dynamics of interceptor therapy on endogenous targets. Together, the experiments detailed below are key for supporting their claim on p. 12 that the selectivity of the compounds for specific peptides in the PTC will be more effective against oncogenes with short half-lives over essential housekeeping genes.\na. Specifically, the authors should test the kinetics of inhibition of Myc or other endogenous targets (these will be better defined by the above proteomics experiments). Currently, the earliest time point of treatment is 2hrs at which time Myc protein level is already quite suppressed.\nb. Also the authors should test the inhibition of endogenous protein expression across a drug titration as shown for RSR signaling in Fig 5. Are the short lived driver oncogenes inhibited at a lower concentration? This can help discriminate between the contributions of ribosomal stress response vs loss of driver oncogene expression for the compounds’ efficacy.\nOther points:\n1. The authors should demonstrate the “on-target” effects of IDB-003 in the in vivo tumorigenesis study. That is, does Myc protein level decrease in the treated tumors?\n2. The manuscript would benefit from additional discussion of potential rules or guidance on how to evolve the compounds to increase selectivity based on the structural data. Additionally, discussion of the relative contribution and interdependency of peptide binding and the A site inclusion would be appreciated and further illuminate the specificity of the molecules for their targets.\n3. The authors discuss the literature on the translation of Myc mRNA and how their work is relevant in this context."}, "author_response": "We thank the reviewer for this comment and have addressed these remarks in a few places in the text to clarify our messaging in the manuscript. In general, we have revised the text to more accurately describe context-dependent activity in relation to MYC. While the interdictors we present here have context-selective activity for select amino acids or amino acid motifs in the ribosome-bound polypeptide chain, our molecules are not single-mRNA selective (i.e., one interdictor inhibits translation of one mRNA), and we realize this may not have been effectively communicated.\nWe believe this comment is addressed by multiple revisions to the text and figures, however we will summarize specific responses to this comment here as well. IDB-001 was designed to inhibit polypeptide sequences with acidic amino acids (D/E), and thus we thought this would be a great proof-of-concept reporter sequence to capture interdictor-peptide interactions in a ribosome nascent chain complex. This was accomplished and is highlighted in Figure 3 where we observe local structural rearrangements in this nascent polypeptide upon interdictor binding. However, as the reviewer noted, IDB-001 has relatively poor inhibition of cell viability compared to IDB-002 (Figure 4) and MYC depletion activity (Supplemental Figure 10) despite the D/E-selective activity we characterized (Figure 1F, 2E). This may be due to subtle differences in ribosome binding kinetics between the molecules, or as mentioned, stronger site(s) in the MYC open reading frame that might be interdicted by IDB-002 leading to a stronger impact on MYC translation. Since IDB-002 impacts the translation of more 4-mers than IDB-001 (Figure 2A-B) we anticipate IDB-002 treatment leads to more robust translation stalling by inhibiting more peptide bond formation events across the MYC open reading frame. Consistent with this, our ribosome profiling shows a greater accumulation of ribosomes near the N-terminus of MYC and in an upstream open reading frame for IDB-002 treatment compared to IDB-001 (shown below). We have revised our language around sequence-preferential activity to de-couple amino acid preferences we observe from the differential MYC depletion of the two molecules. More likely the enhanced activity for IBD-002 on MYC depletion is a result of stronger global activity.\n[Response Figure 1 omitted]\nAlong these lines: how well did Anisomycin inhibit Myc expression?\nWe used HTRF to quantify endogenous MYC depletion in HCC1143 cells across a drug titration for interdictor or anisomycin and found that anisomycin reduces MYC to a similar extent to IDB-002 but is less potent than IDB-003. In contrast, IDB-001 shows little effect at matched concentrations for a short time interval (2 hours). Importantly, we added clarification on the scope of selectivity in the text as mentioned above. The sequence preferences we define operate at the level of short motifs (e.g. -3:-1 context in the PTC) that are shared by many transcripts. MYC still serves as a biologically relevant readout due to its short half-life and the addiction of certain cancers to high MYC expression, but not because it is uniquely targeted by the interdictors we present here.\n[Response Figure 2 omitted]\nAt the beginning of the results, the authors describe the design of the novel compounds very superficially. Was it a purely rational design based on the structure of the ribosome? No molecular dynamic simulations or similar approaches to assist the design? No failed attempts? I have always had the impression that it is really difficult to tailor known molecules to improve/customize their function.\nWe thank the reviewer for these thoughtful comments and have included some more description regarding the structure-based design principles in the intro and discussion. This paper was not intended to include the comprehensive design strategy. Instead, the focus of this manuscript is related to the structural and biological findings for IDB-001, IDB-002 and IDB-003 to provide a foundation for our learnings. We intend to publish a separate and more comprehensive paper that summarizes the details of our structure-based design, SAR observations, and computational approaches.\nThis paper focuses on insights obtained from our high-resolution cryo-EM structures which are the corner stone of our structure-based design efforts. Based on our analysis, the same structure-based drug design principles applied to traditional small molecule modalities are directly relevant to our rational approach to design and optimize interdictors as linker-less heterobifunctional small molecules. Our small molecules bind in the A-site near the nascent polypeptide. This is the narrowest portion of the PTC where the peptide does not have significant conformational freedom, forming predictable backbone and sidechain conformations. These structural observations have been further confirmed by molecular dynamics simulations where the average flexibility of the peptide along the length of the PTC is captured. In addition, the same complementary electronic (hydrogen bonding and hydrophobic) and steric interactions that drive the binding of small molecules to a receptor binding site are also important to the binding of the heterobifunctional small molecules to the rRNA and nascent peptide in the PTC.\nWe apply free energy perturbation (FEP+ as implemented in the Schrodinger software suite) calculations to guide the design and optimization of our small molecules. We can rationalize SAR observations retrospectively, as well as, make successful prospective predictions for new designs. However, for this manuscript, our focus was specifically on IDB-001 and IDB-002, so we did not include additional computational details and SAR. Instead, we highlighted the core design principles for these two specific molecules which were rooted in literature-precedented and well-characterized interaction patterns between small-molecules and amino acids/RNA.\n[Additional references omitted]\nThe in vitro experiments are based on reporter sequences carrying 6 repeats of the stalling sequences. Why 6? Is one or two not sufficient? Maybe it would also be interesting to include the potential stalling sequence of Myc and compare it with the identified motifs. How does in vitro compare to in vivo. It should be possible to create a reporter mRNA with the respective motifs and express them in cells (either directly by RNA transfection or expressed from a plasmid). This would also provide an idea of how strong the inhibition is at certain sites. Perhaps this could also provide an idea about the stalling elements of Myc (the point I raised earlier).\nThe HiBit tag itself is 11 AAs long, and while its sequence is predicted to be a very poor substrate for interdiction with the compounds presented here we wanted to ensure that the majority of the inhibitory signal we measured was derived from the sequence of interest rather than the tag. At the same time we did not want to make the reporters so long that differentiating between them would be difficult given the dynamic range of our assay. We settled on six repeats to achieve these two goals, though certainly slightly more or slightly fewer repeats would also have worked.\nThe primary goal of the reporter assay was to determine the largest extent of the sequence preferences of the two compounds in terms of biochemical drug inhibition parameters to aid in interpretation of the much richer ribosome profiling datasets. As such, we picked sequences with highly confident ribosome-profiling pause scores (i.e., a high number of footprints at that position) and with very different pause scores for the two compounds IDB-001 and IDB-002. This assay can be expanded to any number of reporters but due to the simplifications needed to create a robust biochemical assay, in particularly the use of IRES-driven initiation, it will never perfectly capture the dynamics on complex targets such as Myc (see the answer to point 1 above). We have updated the main text to more clearly delineate the intended role of these measurements.\nOur primary in cellulo readout is ribosome profiling, which measures stalls on endogenous mRNAs and avoids UTR and copy-number artifacts that might come from transgenic expression of reporters. Avoiding such artifacts has proven challenging with simple transfection-based assays, and we believe that the genetic engineering needed to create the required transgenic cell lines to overcome these challenges is outside the scope of this study and the intended role of the biochemical assays within it.\nMaybe I missed it: do the compounds bind the PTC in the absence of stalling motifs or are they required for binding? This might allow us to speculate about the mode of action.\nThe compounds can bind the PTC without a nascent polypeptide chain via the same rRNA contacts that anisomycin leverages for binding. While the nascent-chain interactions are not required for binding, they further stabilize the interdictor-ribosome complex leading to inhibition of elongation kinetics. We have clarified this in the discussion and now describe the rRNA-anchoring effect of the ANS core.\nDo the cell lines tested (22RV1, HCC1143,…) express different levels of Myc, since 22RV1 or LS411 require higher levels of the compound 001?\nRelative to HCC1143, MYC expression across the cell lines is as follows: 22RV1 = 106%, MCF7 = 22%, LS411N = 79% (Ghandi, et al. 2019, Cancer Cell Line Encyclopedia). Based on MYC expression alone, we would hypothesize that MCF7 might be the ‘weakest’ cell line for interdictor treatment, but obviously that is not the trend we observe. However, the relationship between cell viability and interdictor EC is more complex, primarily owing to the fact that our cell killing activity is not derived exclusively from an impact to MYC, as we now show that other short half-life proteins are impacted in cells. The poly-pharmacology of depleting these short half-life oncogenes, as well as inducing ribosome surveillance pathways are likely to contribute to the cell growth inhibition phenotype we observe. We have modified the text regarding these results to remove any direct connections to MYC.\nVery minor:\nPage 1: I don´t know if this intentional but did you mean “selected protein targets” instead of “select protein targets”.\nWe agree this was an error and have addressed this in the text.\n[Reviewer 2 response omitted for brevity]\n[Reviewer 3 response omitted for brevity]\n[Reviewer 4 response omitted for brevity]\n[Reviewer 5 response omitted for brevity]"}, {"round": 2, "reviewer_comments": {"reviewer_1": "My concerns and comments were addressed sufficiently!\nAll the best!", "reviewer_2": "The revised version of the manuscript \"Context-dependent translation inhibition as a novel cancer therapeutic modality\" by Diamond et al. has addressed all our comments on the previous version of the manuscript. The updated structures show reasonable validation statistics and are now adequately described in the text and the figures. Overall, the text is more stringent and clear.\nWith access to all the maps in a clearly organized folder, we identified an additional problem that needs to be addressed. Other than that, we find the revisions to be satisfactory.\nA fast inspection makes us question whether the P-site tRNA modeled in the FTED RNC + IDB-001 structure (code 9O3X) correctly reflects what is mainly present in the complex. The anticodon density suggests that the residue 35 on the P-tRNA should be a purine (currently modeled as a pyrimidine), at the same time, residues 31 and 39 appear to be purine and pyrimidine respectively (currently modeled in the opposite way). We recommend the authors to take a look again at the tRNA density of this structure to confirm which tRNA it is mainly present in the density, and to adjust their interpretation of the tRNA and the nascent peptide accordingly. The other structures appear to be correct.\nMinor comments:\nThe uploaded LSU focus map of 9O3V (MYC without IDB) appears to be shifted and does not fit to the model. The authors should correct this.\nIn the cryo-EM methods and perhaps in Table 1 and Supplementary Table 1, please clarify which classes from 3D classification are used for the final reconstructions and modelling. Based on the numbers that Supplementary Figure 6 shows for the MYC:IDB-001 RNC complex, this seems to be the POST state. In Supplementary Table 1, it is unclear what \"best of\" means for the POST states of IDB-001+FTED and IDB-002+FPAK - please clarify.\nIn the methods, it is stated that \"All data processing was carried out in Cryosparc v4.584 645 and is 646 schematically outlined in Supplementary Figure 7.\" This should probably be Supplementary Figure 6.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "With this revised version, P. Diamond and colleagues have appropriately addressed my previous comments. I believe their work should be published in Nature Communications, although the following sentences should be modified:\n- Lines 331-332: “IDB-002 treatment showed a dose-response to ANS, while IDB-001 displayed modestly weaker activity (Figure 4A)”. I suggest rephrasing this sentence as follows: “IDB-002 treatment showed a dose-response similar to that of ANS, while IDB-001 displayed weaker activity (Figure 4A).” I am not sure that the term “modestly” is appropriate here, since there is a tenfold difference between the doses of IDB-001 and ANS/IDB-002 required to reach 50% cell viability.\n- Lines 371-373 “Indeed, treatment of MCF7 cells with 1 μM IDB-003 led to rapid depletion of MYC and CCND1, with substantial loss evident by 1-2 hours and near-complete depletion by 4-8 hours (Figure 5D).” While this statement is accurate for CCND1 and CHX, the Western blot in Figure 5D does not show a significant decrease in MYC signal after 1–2 hours, nor near-complete depletion after 4–8 hours, when compared to the tubulin signal. However, this description does hold true when using 10 μM IDB-003, as shown in Supplementary Figure 10D. Therefore, I recommend that the authors rephrase this sentence accordingly.", "reviewer_5": "The authors argued that the validation of their ribosomal profiling by mass spectrometry or other means is out of the scope of this work, but I do not agree. It is still unclear how these compounds reduce cancer cell viability in culture and in vivo. Is this due to the reduction of translation of specific oncogenes or the activation of deadly stress? In fact, the title of the manuscript itself, “Context-dependent translation inhibition as a novel cancer therapeutic modality”, emphasis that the context-dependent translation is important as a cancer therapeutic. This indeed would be very exciting, but there is no data to substantiate such a claim without additional experiments to address this important distinction between translation-specific effects versus a general stress response.\nIt appears that the authors are unaware of the existing literature on the role of translation control and cancer, as well as the numerous efforts aimed at targeting translation specificity, which is more prevalent in cancer cells than in normal cells. While targeting ribosome and translation control is an emerging field in cancer biology, and it is important to pursue, this work still falls short of being published in Nature Communications."}, "author_response": "We thank the reviewer for their positive comments, and their note about the FTED-RNC structure. Re-examining the experimental density for this structure, we agree that for the tRNA residues mentioned by the reviewer, base densities could potentially be interpreted in several ways. We have chosen to be conservative in our interpretation of the exact base sequence, considering the biochemical setup of the experiment and the density of the mRNA in addition to the tRNA density itself, for several reasons:\nFirst, tRNAs are significantly more dynamic, and less rigid, than the surrounding ribosomal RNA and their local resolution is commonly lower than the overall resolution of the structure. Further, the distinction between purines and pyrimidines can be difficult to determine as base pair hydrogen bonding can contribute to density, and base modifications common in tRNAs can distort base shape.\nSecond, while we have done our best to biochemically isolate a homogeneous cryo-EM sample, and performed extensive particle sorting, the particle set could still include a small fraction of ribosomes containing unintended tRNAs from the lysate. Even a small fraction of such ribosomes could contribute ambiguity in the tRNA density.\nThird, in this structure the density for the mRNA extends towards the 5’ end but not past the decoding site. This suggests that the structure, like the other 3 RNC structures, is stalled on the last codon of the message, in line with the experimental design.\nHowever, after reviewing the referee’s concerns and re-examining the experimental maps, we have decided to move the FTED structure to the supplement of the manuscript (Supplementary Figure 8A) and include a note about the limitations of this map in the text. Since all conclusions derived from the FTED structure in the presence of IDB-001 overlap with those from the QEDE structure plus IDB-001, this modification does not affect any conclusions or results presented in the study.\n[Minor comments responses omitted]"}, {"round": 3, "reviewer_comments": {"reviewer_2": "All minor comments have been addressed in a satisfying manner.\nHowever, the major comments on the FTED structure have not been addressed in a satisfying manner by moving this structure to the supplement and stating that \"However, some ambiguity remained in the density-based distinction of three purine/pyrimidine bases in the aspartyl-tRNA of the FTED RNC, possibly because of impurities in the sample.\" The authors write in the answers that \"We have chosen to be conservative in our interpretation of the exact base sequence, considering the biochemical setup of the experiment and the density of the mRNA in addition to the tRNA density itself\", which does not at all make sense.\nIt has to be clarified that in this structure, the peptide sequence in the PTC and its interactions with the inhibitor (i.e. the focus of this study) are inferred from the tRNA species, not the other way around. While there may be some ambiguity, the cryo-EM map clearly shows that the major tRNA present in the complex is different from the one modelled; i.e. stalling does not mainly occur where they expect. This in turn means that the peptide modelled is not the dominating peptide present in the PTC of this complex. Thus, the current description is misleading. The authors have the choice to either re-model and re-interpret the structural data based on the density (i.e. purine-pyrimidine pattern) for the tRNA and mRNA to figure out where this complex has stalled and build the resulting peptide in the PTC or to remove this structure from the manuscript.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "We thank the reviewer for their comments and have decided to remove the FTED RNC structure from the manuscript out of an abundance of caution. All conclusions drawn from the FTED RNC structure overlap with those from the QEDE RNC structure, so its removal does not affect the conclusions or main results of the study. We thank the reviewer for their detailed comments here and throughout the revision process."}]

Decision letter